UQ Exeter Institute Joint PhD

Project team

UQ – Dr Skye Doherty
Exeter – Dr Iain Soutar

Project description

A future of unreliable energy is plausible. Major shifts in peak demand, changing weather patterns and aging infrastructure, combined with the insatiable demand of data centres, means disruption could become a feature of our networks as grids transition to renewable sources. In both Australia and the United Kingdom, the shift from fossil fuels to renewables is underway, however the cost of the transition is high, pushing up prices for households. Meanwhile, there are concerns that rising demand will result in energy shortages.   

Despite the urgency of the energy transition there is a fundamental misunderstanding among key players of the needs and values of others. Energy consumers, policymakers, and industry operators have different, and at times conflicting, priorities. Research suggests that sensory and immersive virtual experiences can encourage deeper connection and empathy with environmental issues, which in turn, can support behaviour change. As a result, there is an opportunity to design interventions that support diverse groups to engage with the multiple perspectives, complex trade-offs and potential consequences of building a sustainable energy future with a view to encouraging act in response.  

This project aims to explore how sensory experiences can be designed to support engagement with the need for and implications of energy transitions. It will engage communities and stakeholders in both countries. The key research questions are: 

• What are the key tensions, values and opportunities related to energy transitions among communities in Australia and the UK?
• How can sensory experiences be designed to engage publics in understanding energy transitions? and taking positive action in response?

Approach

This is primarily a human-centred design project in which the PhD student will undertake both qualitative contextual and participatory research as well as technological prototyping and evaluation.

The project will have three phases:  

Contextual inquiry: a review of existing research on the intersection of immersive technology and social change will inform a series online focus group discussions with stakeholders in the energy sector, specifically policy makers, regulators, providers and consumers in both countries. This work, ideally done in both countries, will identify tensions and opportunities regarding energy transitions and build early engagement with the project.   

Design and initial evaluation: Initial design concepts, informed by phase one will be initially developed by the researcher and refined through co-design workshops and prototyping with groups in each country. One or more identified for further development, implementation and evaluation.   

Analysis and translation: This phase will focus on data analysis and translation. Key insights and findings will be presented back to participants, including industry groups, along with a public-facing report on the actions consumers, policymakers and operators might take, individually or collectively, to build a more resilient energy future.  

 The project will enhance our understanding the role of technology in building empathy among stakeholders in response to contested issues. 

Project outputs include: 

• A high-quality interdisciplinary thesis bridging technology design, energy transition and sustainability.
• Up to three peer-reviewed publications 
• Public facing report and external engagement with stakeholder groups   

Contact

Questions about this project should be directed to Dr Skye Doherty at s.doherty@uq.edu.au.

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Project team

UQ – Dr Wayes Tushar
Exeter – Dr Carolyn Peterson

Project description

Research Problem

Despite the strong potential of agrovoltaics to improve sustainability in energy-intensive agricultural systems, current implementations are predominantly designed at the single-farm level and do not adequately address community-scale integration, energy sharing, and participatory governance. As a result, key challenges—such as perceived land-use competition, mismatches between local energy supply and demand, limited transparency in benefit distribution, and insufficient community acceptance—continue to hinder large-scale deployment and impact. There is a lack of integrated frameworks that combine technical design, economic optimisation, and socio-cultural considerations to enable networked, community-oriented agrovoltaic systems that reliably supply agricultural loads while equitably sharing benefits among stakeholders and support decarbonisation objectives and the transition toward more sustainable and equitable rural energy systems.

Significance

This research addresses a critical gap in current agrovoltaics scholarship by moving beyond predominantly single-farm implementations toward the design and evaluation of community-integrated, networked agrovoltaic systems. Although agrovoltaics is widely recognised as a promising pathway for improving sustainability in energy-intensive agriculture, limited attention has been given to how multiple farms and rural households can be coordinated through energy sharing while ensuring technical reliability, economic viability, and social acceptance.

The project will generate original contributions to knowledge by developing an integrated framework that jointly considers farm types, system architecture, energy management, and socio-economic design for community-oriented agrovoltaics. In doing so, it will advance theoretical and methodological understanding of how distributed renewable generation can be co-optimised with agricultural energy demand and participatory benefit-sharing mechanisms at scale.

From an applied perspective, the research will provide practical design and decision-support tools for reducing irrigation energy costs, improving farm profitability, and enhancing resilience to grid disruptions through locally produced renewable energy. The outcomes will also inform policymakers and industry stakeholders on scalable models for deploying community-based agrovoltaic systems, thereby supporting decarbonisation objectives and the transition toward more sustainable and equitable rural energy systems.

Research Aim and Research Question

The overall aim of this project is to design, develop, and evaluate a community-integrated agrovoltaic framework that enables efficient energy self-sufficiency in irrigated agriculture by optimally coordinating electricity generation, distribution, and sharing among multiple farms and rural households, while addressing technical, economic, social, and cultural challenges to ensure sustainability, profitability, and resilience.

In doing so, the project will address the following research questions:

1. How can a community-oriented agrovoltaic system be technically designed to supply electricity for irrigation and on-farm processing while enabling energy sharing among neighbouring farms and rural households?
2. What energy management and optimisation strategies can effectively balance local supply and demand in networked agrovoltaic communities under varying climatic and agricultural conditions?
3. What are the economic impacts of community-based agrovoltaics with energy sharing on irrigation energy costs, farm profitability, and community-level revenue generation?
4. How do different benefit-sharing and ownership models and farm types influence community acceptance, participation, and perceived fairness in agrovoltaic projects?
5. What technical, economic, social, and cultural barriers and enablers affect the large-scale adoption of community-integrated agrovoltaic systems?

The proposed research approach and methods

The proposed research will be conducted in the following three phases:

1. Techno-Economic Modelling of Networked Farms: In the first phase, a techno-economic model of networked agrovoltaic farms will be developed without energy-sharing capabilities. The objective is to determine optimal local solar configurations—either solar-only or solar-plus-battery—for each farm, taking into account farm type, size, energy demand, and socio-economic characteristics. This phase will generate scenarios identifying potential energy “gensumers” (farms that both generate and consume electricity) and energy consumers to inform the design of the energy-sharing framework in Phase 2. A coalition formation game [1] will be employed to explore feasible groupings of farms for future energy sharing and to guide decisions on energy asset allocation. Agricultural data from the Department of Agriculture, Fisheries and Forestry (Australia) and the Centre for Rural Policy Research (CRPR) will be used, complemented by semi-structured interviews with farmers at the Sunday Farmers Market to capture in-depth insights into farming activities, energy requirements, and associated costs.
2. Design of Community Energy Sharing Framework: Phase 2 will focus on developing a novel, game theory-based energy-sharing algorithm [2] for the networked farms identified in Phase 1. The framework will enable farms and rural households to exchange electricity based on local sharing prices, supply-demand conditions, and grid energy costs. Cooperative game theory [3] will be applied to ensure fair benefit allocation and socially optimal outcomes for all participants. A key innovation of this phase is the integration of farm types and seasonal energy demand variations into the energy-sharing decision-making process. For example, farms with surplus energy may choose to share it with neighbours, while those anticipating higher future demand may store energy for later use, depending on current prices and community needs.
3. Model Validation and Stakeholder Evaluation: The final phase will validate the networked agrovoltaic and energy-sharing model through extensive simulations across multiple crop types and climate scenarios. Farmer surveys will be conducted to evaluate feasibility, acceptance, and potential barriers from the stakeholder perspective. This phase will be iterative, with feedback from farmers informing adjustments to the energy-sharing model to ensure alignment with practical needs and principles of participatory governance [4]. The outcomes will provide evidence-based recommendations for policymakers and industry stakeholders on scalable and socially acceptable models for community-integrated agrovoltaic systems.

Project Deliverables

Techno-Economic Model of Networked Agrovoltaic Farms: A robust modelling framework will determine optimal solar and battery sizing for different farm types, identify potential energy “gensumers” and consumers within networked farms, and capture the socio-economic and agricultural factors influencing participation in energy sharing.

Game Theory-Based Energy Sharing Framework: A novel cooperative game-theoretic algorithm will enable electricity sharing among farms and rural households by integrating farm type, seasonal energy demand, and dynamic pricing, supported by a decision tool that ensures equitable benefit distribution and maximises community-level energy efficiency.

Simulation and Policy-Relevant Recommendation: Validation of the agrovoltaic network and energy-sharing model across multiple crop and climate scenarios, combined with farmer surveys to assess feasibility and acceptance, leading to evidence-based recommendations for policymakers and industry on scalable community-integrated systems.

Knowledge sharing

This project is anticipated to contribute pioneering outcomes to networked agrovoltaic relevant literature through its techno-economic-driven, game-theoretic approach, with potential applications in agricultural settings beyond the selected test system. The project’s early results will be shared with agricultural stakeholders and academic audiences through webinars, virtual seminars, international conferences, and targeted workshops. The PhD student will also publish high-impact research outputs to leading Q1 journals in the energy and social science, such as Nature Energy, Energy and Social Science, and Energy and Environmental Science. In addition, the project’s outcomes will be actively promoted through UQ and the University of Exeter’s social media channels to engage a broader, non-academic audience.

References

[1] Tushar et al., “A coalition formation game framework for peer-to-peer trading,” Applied Energy, vol. 261, pp. 114436:1-13, Mar 2020.

[2] Tushar et al., “Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges,” Applied Energy, vol. 282, Part A, pp. 116131:1-19, Jan. 2021.

[3] Saad et al., “Coalitional game theory for communication networks,” IEEE Signal Processing Magazine, vol. 26, no 5, pp. 77-97, Sept. 2009.

[4] Jager et al., “Pathways to implementation: Evidence on how participation in environmental governance impacts on environmental outcomes,” Journal of Public Administration Research and Theory, vol. 30, no 3, pp.383-399, 2020. 

Contact

Questions about this project should be directed to Dr Wayes Tusher at w.tushar@uq.edu.au.

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Project team

UQ – Dr Kieren Lilly
Exeter – Professor Cornelia Guell

Project description

Research Problem and Significance

Climate change represents a critical global public health emergency, with escalating frequency and severity of climate hazards worldwide. Systematic reviews have documented extensive adverse health outcomes following climate events—including heatwaves, floods, and droughts—spanning increased all-cause mortality, infectious disease incidence, hospitalisations for respiratory, neurological, and cardiovascular conditions, and deteriorating mental health. Beyond direct physiological impacts, exposure to climate events significantly elevates health threat perceptions. With policy trajectories projecting global temperatures to rise by up to 4.0°C above pre-industrial levels by 2060, a substantial proportion of the global population faces imminent health risks. Notably, almost one-third of UK residents and two-thirds of Australians have experienced a climate event within the past five years, underscoring the urgency of this issue.

Despite growing recognition of climate-related health threats, significant gaps remain in understanding how local health and social care provision can be compromised through climate hazards, and how communities prepare for and respond to these events. Health-related preparedness represents a key strategy for building community resilience and informing government mitigation policies. However, the frequency, severity, and health impacts of climate events vary considerably across global regions and are not uniformly distributed. Social, environmental, and physiological vulnerabilities create differential exposure and susceptibility patterns at both individual and population levels. This heterogeneity necessitates comparative research across diverse contexts to distinguish context-specific factors from universal determinants of climate resilience.

The specific research objectives are

1. To systematically examine community experiences of climate events in the UK and Australia, identifying health impacts, preparedness practices, and infrastructure vulnerabilities
2. To develop a place-based climate resilience framework to healthcare provision that integrates social, environmental, and health determinants across different geographical and cultural contexts
3. To create a geospatial climate preparedness mapping tool that visualises vulnerability hotspots and resource allocation priorities
4. To generate evidence-based recommendations for policy and practice that protect local healthcare delivery and enhance community-level climate resilience

Research Approach and Methods

This study adopts a mixed-methods, comparative case study design that leverages the complementary climate experiences (Flooding, wildfire, heatwave and drought) of UK and Australian communities across the following three stages:

1. Case studies: Qualitative data collection to examine community experiences of climate events, identifying health impacts, preparedness practices, and infrastructure vulnerabilities.
2. Desk top enquiry and user testing: Literature review to develop a place-based climate resilience framework.
3. Quantitative GIS analysis: Create geospatial preparedness mapping tool to highlight vulnerability hotspots and resource allocation priorities.

Both nations are experiencing increasing climate event frequency and severity, yet differ in climate hazard profiles, healthcare infrastructure, and policy environments—providing rich comparative contexts for identifying transferable versus context-dependent resilience factors.

The research will employ a sequential explanatory design informed through interdisciplinary perspectives of geography and public health, and combining quantitative geospatial analysis with qualitative community engagement to develop a comprehensive understanding of climate preparedness needs and capacities. A dissemination strategy will include Arc StoryMaps, Academic journals, policy briefs and stakeholder workshops.

Contact

Questions about this project should be directed to Dr Jonathan Olsen at j.olsen@uq.edu.au.

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Project team

UQ – Professor Antje Blumenthal
Exeter – Professor Gordon Brown

Project description

Infections – A Persistent Global Health Challenge

Infectious diseases remain a major cause of illness and death worldwide. Chronic infections are especially challenging, often requiring long and complex treatment regimens that can lead to substantial side effects. These challenges are intensified by rising antimicrobial resistance, which reduces the effectiveness of existing drugs and limits prospects for cure. The World Health Organization has identified tuberculosis, caused by Mycobacterium tuberculosis, and fungal infections, including those caused by Candida species, as high‑priority threats in urgent need of improved treatment strategies. One promising frontier is the development of therapies that strengthen immune defences. To realise this potential, we must better understand how the immune system detects and controls pathogens.  

Project Opportunity

This project builds on exciting new discoveries revealing a previously unrecognised mechanism through which the innate immune system identifies both mycobacteria and fungal pathogens. For the first time, we will define the molecular and cellular features of this shared recognition pathway and determine how it contributes to early host defence. By clarifying how this mechanism operates across pathogen classes, the project lays the foundation for developing broad spectrum immune‑enhancing treatments that could shorten therapy and improve patient outcomes in hard-to-treat infections.  

Aims

The overarching aim is to characterise this newly discovered shared immune recognition pathway and its role in controlling infection. Specifically, the project will:  

1. Map the host cell responses triggered by Mycobacterium tuberculosis and Candida albicans via this shared innate immune mechanism.  Using in vitro experimental systems, this work will map cellular immune responses and effector pathways.  
2. Determine how this new pathway interacts with established immune recognition pathways during mycobacterial and fungal infection.  This work will determine the cellular receptors and their intracellular signalling mechanisms.
3. Define contributions of the new pathway to immune responses and pathogen control during fungal infection and compare these findings with its emerging roles in mycobacterial infections. Using in vivo models, this work will dissect underlying immune mechanisms and their overlap with anti-mycobacterial immunity.   

Methods

To address these aims, we will use in vitro and in vivo infection models; generate and employ genetically modified cellular systems; and apply biochemical, cell biological, and immunological approaches to map intracellular signalling pathways and host responses to infection. To enhance the translational potential of the project outcomes, clinical strains of Mycobacterium tuberculosis and Candida albicans will be integrated into the investigations.    

Outcomes and Deliverables

By uncovering a shared mechanism of immune activation, this project will deliver fundamental insights into how the host mounts early defences against mycobacterial and fungal pathogens. These findings have the potential to identify new broad spectrum therapeutic targets and guide the development of host‑directed interventions that complement existing antimicrobial treatments. Such approaches could accelerate or enable novel approaches to treat tuberculosis and severe fungal infections, which impose substantial global health and economic burdens. Because the pathways investigated include both validated and emerging drug targets, the project will provide a strong basis for future translational and therapeutic development.

Contact

Questions about this project should be directed to Professor Antje Blumenthal at a.blumenthal@uq.edu.au.

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Project team

UQ – Dr Leslie Roberson
Exeter – Associate Professor Kristian Metcalfe

Project description

Research problem and significance

Sharks and rays are among the most threatened vertebrates globally, with over one-third of species at risk of extinction, primarily due to overfishing. While international attention has focused on the luxury fin trade, a growing share of shark mortality is driven by small-scale fisheries, where elasmobranchs support food security, livelihoods, and local economies [1]. These fisheries are widespread and poorly regulated, yet remain underrepresented in quantitative research [2]. 

Current management approaches have struggled to curb declines partly because they typically assume all fishers operate similarly and respond uniformly to regulations or market signals. Small-scale fisheries, however, are characterised by high levels of individual decision-making constrained by strong economic and social constraints linked to food security, market access, and risk. Fishers make daily choices about species targeting, fishing locations, and gear use that directly influence shark and ray catch [2]. These choices are shaped not only by ecological conditions and regulations, but also by prices, social norms, and accumulated skill and experience3. Treating fishers as a uniform group obscures this behavioural complexity and limits intervention effectiveness, especially where enforcement capacity and resources are lacking. 

[1] Doherty, Metcalfe, et al. (2023) Artisanal fisheries catch highlights hotspot for threatened sharks and rays in the Republic of the Congo. Conservation Science and Practice, doi:10.1111/csp2.13017

[2] Roberson, Klein, et al. (2022) Spatially explicit risk assessment of marine megafauna  vulnerability to Indian Ocean tuna fisheries. Fish and Fisheries doi:10.1111/faf.12676.

[3] Roberson, Klein, et al. (2024) Opportunity to Leverage Tactics Used by Skilled Fishers to Address Persistent Bycatch Challenges. Fish and Fisheries, doi:10.1111/faf.12873.

[4] Roberson & Wilcox (2025). Fishery bycatch rates largely driven by variation in individual vessel behaviour. Nature Sustainability, doi:10.1038/s41893-025-01602-z

Research aims

This PhD project aims to characterise differences in fisher behaviour and performance to identify behaviourally informed pathways for reducing unsustainable shark and ray catch without undermining livelihoods. Using four fishery case studies representing a range of shark fishing contexts, the project will: 

1. Quantify individual variability in elasmobranch targeting within and across small-scale fisheries (Publication #1: Peru-Pakistan-Congo comparison)
2. Assess how market prices interact with social and operational drivers of fishing behaviour (Publication #2: Congo/Cote d’Ivoire market and landings data)
3. Examine whether and how fishers adjust targeting over time in response to species rarity, regulation, or environmental change; (Publication #3: Congo longitudinal study) 
4. Identify leverage points for management interventions aligned with fisher decision-making with stakeholders and local project partners (Publication #4: Perspective piece).

Research approach and methods

Research will be carried out under the supervision of Dr Leslie Roberson and Associate Professor Carissa Klein at the Centre for Biodiversity and Conservation Science at The University of Queensland and under the supervision of Dr Kristian Metcalfe at the Centre for Ecology and Conservation at the University of Exeter.

The project adopts a comparative, interdisciplinary research approach, integrating fisheries science, behavioural ecology, and applied economics. Analyses will draw on high-resolution, longitudinal datasets from four complementary case studies: large “small-scale” multispecies gillnet fisheries in the northern Indian Ocean and South America; and multi-gear artisanal shark fisheries in West and Central Africa. Advanced statistical models (e.g. mixed effects models in both frequentist and Bayesian frameworks) will be used to disentangle individual behavioural effects from environmental, seasonal, and gear-related drivers of catch, and to assess behavioural responses to economic signals where market data are available.

Project deliverables and contribution to knowledge

Key deliverables include three peer-reviewed publications in leading fisheries, sustainability, and conservation journals, alongside policy-relevant outputs for managers and conservation practitioners. The project will advance understanding of behavioural heterogeneity in fisheries, demonstrate how individual agency shapes exploitation patterns, and provide one of the most comprehensive comparative analyses of shark fishing in small-scale fisheries to date. More broadly, it will generate transferable insights for managing vulnerable species in fisheries globally, including in resource-limited, food-security-dependent fishery contexts.

Contact

Questions about this project should be directed to Dr Leslie Roberson at l.roberson@uq.edu.au.

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Project team

UQ – Associate Professor Sarit Kaserzon
Exeter – Professor Edward Keedwell

Project description

Ensuring water security is a critical global challenge, underscored by UN Sustainable Development Goals 6 and 3 (Clean Water and Sanitation; Good Health and Well-being). The increasing incidence and diversity of drinking water contaminants necessitates advanced mitigation strategies. This project aims to pioneer a screening approach using High-Resolution Mass Spectrometry (HRMS) and Machine Learning (ML) to identify contaminant hazards in water sources for more rapid and comprehensive risk assessment and mitigation. By integrating environmental science, analytical chemistry, data science, AI and engineering, and collaborating with the UK and Australian water industries and the Queensland Health Department, this project aspires to develop a revolutionary water management risk assessment tool for enhanced water security. Anticipated outcomes will significantly impact societal, economic, environmental, and public health sectors, benefiting communities.  

The project concept emerged from the water and health industries’ need to address threats in drinking water supplies. It was conceived during the Brisbane G20 summit, where the water industry approached UQ to design a potable water monitoring and security framework for Brisbane’s drinking water supplies. A proof-of-concept was developed, focusing on anomaly detection in water supplies, rather than investigating each, which is currently infeasible. The proposed solution included fingerprinting a ‘typical’ water sample and identifying ‘anomalies’, similar to automated tools used to detect cancerous cells in tissue samples. Advances in HRMS instruments and adaptive ML models, have made it possible to envision such a modernised water security tool. 

The project leverages UQ-Exeter strengths in Environmental Science and Data Science through the Queensland Alliance of Environmental Health Science (QAEHS) and the Institute for Data Science and Artificial Intelligence, and the CIs ongoing and substantive work within the Australian and UK water industry. UQ is the preeminent Australian university in environmental sciences, ranked 15th in the 2025 QS world rankings, while Exeter is ranked 36’s, 33rd globally for SDG6 Clean Water and Sanitation. QAEHS has established rigorous HRMS protocols while Exeter’s Institute provides proven computational solutions for the water industry and links with the centre for resilience in environment, water and waste (CREWW).

The project aligns with UQ and Exeter’s strategic goals: (UQ’s Toward 2032) to deliver mission-driven research aligned with industry, government and community priorities, fostering partnerships for research translation and commercialisation to create positive impact, and (Exeter’s Strategy 2030) to work across teams and disciplines to tackle societal challenges and ensure research is translated for public good.

Contact

Questions about this project should be directed to Associate Professor Sarit Kaserzon at k.sarit@uq.edu.au.

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Project team

UQ – Dr Nathan Fox
Exeter – Professor Julian M. Ortiz

Project description

Global demand for the metals required for the green energy transition is expected to exceed supply by the mid‑2030s. Addressing this shortfall depends on reducing the uncertainty and risk that currently limit the technoeconomic, environmental and social viability of mining projects. Orebody knowledge (OBK), enabled by integrated technologies, provides a foundation for this by measuring geological heterogeneity at multiple scales to better understand the controls on uncertainty. Geometallurgy operationalises OBK by translating this heterogeneity into predictive spatial models that reduce technical risk and optimise strategic mine planning.

Sensor‑based technologies, including XRF, hyperspectral imaging, LIBS and CT/XRT, enable rapid, multi‑scale analysis of intrinsic chemical, mineralogical and petrophysical variability. These tools are increasingly used in exploration for drill‑core characterisation, grade monitoring and sensing/sorting applications. However, their uptake in geometallurgy remains limited due to the high uncertainty associated with geostatistical modelling of sparse, multivariate datasets. Integrating these technologies across the mining value chain, from early characterisation through to processing, has the potential to generate critical geological information that strengthens geometallurgical and waste domaining. Within a circular‑economy framework, this integration can reduce energy consumption, improve metallurgical recovery and lower environmental liabilities.

This project will develop an open‑source framework for the systematic collection, validation and spatial geometallurgical modelling of sensor‑based characterisation data, enabling optimisation of the strategic mine plan from the earliest stages of the life‑of‑mine.

The project’s objectives are to:

1. Develop a roadmap embedding advanced characterisation technologies across the life‑of‑mine to improve metallurgical performance and geoenvironmental stewardship.
2. Use statistical and machine‑learning methods to correlate sparse, costly geometallurgical and geoenvironmental tests with variables measured rapidly and economically using sensor technologies.
3. Quantify uncertainty in these variables and create geostatistical workflows and dynamic block models that propagate predicted geometallurgical and geoenvironmental responses across the strategic mine plan. 
4. Support waste‑reduction strategies by identifying ore‑sorting amenability that upgrades feed grade, reduces tailings footprints and creates reuse opportunities within a circular‑economy framework.

With access to a dedicated Evolution study site, the project will integrate existing geological and metallurgical datasets with new core‑scanning data generated by Australian providers (CSIRO, Veracio, Corescan, GeologicAi). Representative samples will be selected using multivariate geostatistical domaining and validated through mineralogical, chemical and textural analyses (TIMA, SEM, XRD, XRF) and metallurgical/geoenvironmental tests (SMC, BBWi, flotation, ABA) at UQ’s CMM‑NRICH facilities. Sensor‑based ore‑sorting trials will be undertaken at the University of Exeter to assess upgrading potential and waste‑reuse opportunities.

The University of Exeter will lead the development of machine‑learning‑enabled geostatistical approaches to quantify uncertainty in geological, textural and geometallurgical variables derived from core scanning. These will be incorporated into spatial block and stochastic models to identify value drivers and risk factors linked to geological heterogeneity.

The project will advance cross‑disciplinary knowledge by demonstrating the value of integrated sensor‑based technologies in geometallurgical modelling, reducing operational and geoenvironmental risk from exploration through to closure. Its open‑source outputs will ensure workflows and case studies are widely accessible, supporting technology uptake and contributing to a more sustainable mineral supply.

Contact

Questions about this project should be directed to Dr Nathan Fox at nathan.fox@uq.edu.au.

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Project team

UQ – Dr Kamila Svobodova
Exeter – Dr Yasser Mehrani

Project description

The global shift to sustainable energy is accelerating mineral extraction, with large-scale mining projects rapidly emerging, expanding and closing across regions [1]. These dynamics drive demographic change through employment, land-use change and resettlement [2]. Despite their pervasiveness, the demographic changes remain difficult to identify and systematically assess. No spatially explicit datasets exist to map them, which limit the capacity of planning, regulation and industry standards to anticipate and mitigate impacts. Existing research either maps broad global patterns [1,2] or isolated case studies [3], leaving mining-related demographic change largely invisible in decision-making.

Project Aims

This project aims to develop an innovative assessment framework to identify and spatially localize mining-related demographic changes. It will provide the first globally geolocated dataset of these changes. Using a two-stage approach, the project first undertakes global quantitative analysis to identify demographic changes associated with large mining projects. These patterns then guide the selection of two study regions in Australia and the UK, where finer-scale quantitative analysis is combined with qualitative research. This mixed-methods approach enables interpretation of the mechanisms underlying observed global patterns.

Project Objectives

The project has four objectives:

1. Build a global geospatial typology of large mining projects for comparative analysis: Operating large mining projects will be clearly defined to guide systematic data collection from global datasets (S&P Capital IQ Pro; ICMM; [4]). Key project attributes (e.g., method, commodity, life stage, size) will be classified into a coherent typology, producing a geodatabase as the primary outcome.
2. Model global mining-related demographic change using spatial and temporal indicators: The analysis will identify areas experiencing demographic change between 2014 and 2026 and statistically link observed patterns to mining projects. Infrastructure and settlement expansion and densification will be quantified using multi-temporal Sentinel-2, -1 and Landsat via machine learning and change-detection techniques (e.g., Random Forest) and statistically modelled against mining project characteristics using panel regression and econometric models. Where available, census and labour data will validate and calibrate these indicators. The analysis will be conducted using finer-scale data in one Australian and one UK study region. 
3. Identify indirect demographic effects and functional mining regions in study regions: Company records, workforce mobility data and supply-chain analyses will be used to identify contractor catchments and commuting corridors to reveal how mining reshapes settlements and labour markets beyond host communities. The outcome is a transferable framework that delineates functional mining regions as empirically derived labour–economic zones. 
4. Contextualise spatial-demographic evidence through participatory mapping (PPGIS) in study regions: Findings from O1-O3 will be contextualised through semi-structured interviews and PPGIS with ~30 stakeholders per region (industry, local governments, community members), with ethics approval secured prior to data collection. Sampling will aim for diversity across gender, age, stakeholder group and proximity to mining. PPGIS will spatially identify perceived demographic vulnerabilities and lived experiences of mining-related change. O4 will deliver a decision-support framework translating spatial-demographic evidence and stakeholder knowledge into policy recommendations.

[1] Svobodova et al. (2022). https://doi.org/10.1038/s41467-022-35391-2

[2] Owen et al. (2021). https://doi.org/10.1016/j.exis.2021.01.012

[3] Svobodova et al. (2021). https://doi.org/10.1016/j.erss.2020.101831

[4] Maus et al. (2022). https://doi.org/10.1038/s41597-022-01547-4

Contact

Questions about this project should be directed to Dr Kamila Svobodova at k.svobodova@uq.edu.au.

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Project team

Exeter – Associate Professor Gavin Buckingham
UQ – Dr Jarrod Knibbe

Project description

Research Problem and Significance 

Virtual Reality (VR) represents a disruptive shift in the modern training ecosystem, increasingly adopted across healthcare, defence, and manufacturing. However, a critical human-centred design challenge emerges: users typically interact with these virtual environments through controller-based interaction, which is largely devoid of the haptic (touch-based) cues that are a core part of real world interactions. The consequences for embodied learning without haptic feedback in digital environments remain largely unknown. As VR training proliferates across sectors, establishing evidence-based principles for haptic design is paramount for responsible innovation. 

Relatedly, literature in motor control suggests that proprioception is a primary driver of skill acquisition. Seminal work by Wong and Gribble (2012) demonstrated that passive proprioceptive training—where the limb is moved by a robot—can induce significant improvements in active motor performance. This implies that “feeling” the correct movement can be a mechanism to improve skill learning, akin to the far larger body of work on observational learning in surgery (e.g., Lebel, Haverstock, Cristancho, van Eimeren, & Buckingham, 2018).   

Research Aims and Objectives  

1. To determine which haptic cues are critical to optimize sensorimotor learning in surgical contexts.  
2. To investigate if proprioceptive cues delivered though a haptic device to guide the user through ideal trajectories can replicate the learning benefits observed in fundamental motor control research within a complex VR surgical tasks.
3. To establish evidence-based design principles for haptic feedback in VR training systems, using surgery as a test-case  

Proposed Research Approach and Methods 

At Exeter, the candidate first will conduct a series of experimental tasks using 3D Systems Phantom Touch devices (robotic arms which provide force feedback of simulated physical contact while measuring movement kinematics and force output). These will be integrated with bespoke VR simulations of surgical tasks developed in collaboration with our industry partner, FundamentalXR, adapted to be delivered with and without haptic cues. Then, at UQ the candidate will work with computer scientists to design paradigms that compare “active” learning (standard VR) against “proprioceptive” learning (haptically guided movement), measuring outcomes such as path efficiency, force consistency, and transfer of training to novel tasks.   

Originality and Innovation

This project is highly innovative in applying fundamental theories of human motor control to address a critical gap in immersive training design. It moves beyond the current standard of visual-dominant VR to a multisensory approach that respects the physicality of surgical practice, enabled by an interdisciplinary team combining Experimental Psychology, Computer Science, and Clinical Surgery.  

Deliverables and Contribution to Knowledge 

The outcomes will serve as a roadmap for the next generation of how haptic feedback can underpin VR in surgery and beyond. We expect this work to yield high-impact publications and support follow-on funding applications to the EPSRC or Innovate UK regarding haptic technologies in healthcare and wider tele-robotics.

Contact

Questions about this project should be directed to Associate Professor Gavin Buckingham at G.Buckingham@exeter.ac.uk.

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Project team

Exeter – Professor David Phillips
UQ – Dr Mickael Mounaix

Project description

The next generation of signal processing, computing and artificial intelligence (AI) technologies will be unlocked by the close integration of electronics and photonics. This project will deliver a new ultra-fast laser fabrication system capable of creating three-dimensional (3D) networks of waveguides in a few hundreds of femto-seconds, providing a scalable path to photonic network integration for emerging low-energy opto-electronic AI systems and beyond.

The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms can solve. While conventional electronic information processors are exceedingly well-developed, their capabilities are being rapidly outstripped by the rapid rise of AI: both the training and inference phase of electronic neural networks is highly power-intensive, and their widespread use puts ever-increasing pressure on global energy infrastructure [1].

Photonic circuits guide and process light-based signals in the optical domain [2]. Photonics is set to became a major part of future AI systems, due to its inherently low energy consumption, high-speed data transfer and vast potential for parallelisation. Signals are already carried between electronic processors in the optical domain in the form of high-speed fibre optic internet, inter-satellite laser communications, and optical interconnects across data centres. These optical connections will become ever shorter and more integrated with electronic systems, and will not only connect, but also process information themselves. This level of integration calls for scalable fabrication technologies which poses a critical challenge: connectivity is needed in 3D while conventional lithography is intrinsically 2D. 

Ultra-fast direct laser writing uses femtosecond pulses of focussed light to structure materials in 3D [3, 4]. By scanning a high-power laser beam through a medium, it can ‘draw’ 3D networks of waveguides (freestanding or embedded within a glass substrate), and more complex optical components [3,4]. Direct laser writing has enormous potential to address photonic integration challenges. Yet at present structures are slowly created one voxel at a time. Our project moves from sequential to parallel laser writing, increasing fabrication rates by up to two orders of magnitude.

Our vision: We will combine advanced spatio-temporal beam shaping technology developed by Mounaix at UQ [5, 6] with the high-speed laser beam shaping [7-9] and direct laser-writing capabilities [3,4] of Phillips at Exeter. By intricately shaping single fs-laser pulses in space, time and polarisation, elaborate beam shapes will be created that rapidly laser fabricate optical components within a few hundred femtoseconds. Our demonstrator system will allow near-arbitrary structures to be dialled up by the user, offering a versatile and highly scalable laser fabrication tool for next-generation photonic technologies.

[1] Momeni, Ali, et al. (2025) Nature 645.8079.

[2] Bogaerts, W. et al. (2020) Nature 586(7828).

[3] Būtaitė, U. G., …& D.B. Phillips (2019). Nature Communications 10(1).

[4] Būtaitė U.G., …& D.B. Phillips (2026). arXiv:2602.07222

[5] Mounaix, M. et al. Nature Communications (2020) 11(1).

[6] Komonen, A.V., …& M. Mounaix. (2025) arXiv:2506.20365. [under review at Nature Photonics]

[7] Stellinga, D., D.B. Phillips et al. (2021) Science 374(6573).

[8] Rocha, J.C., …& D.B. Phillips (2025). Nature Communications 17(73).

[9] Mididoddi, C.K., …& D.B. Phillips (2025). Nature Photonics 19(4).

Contact

Questions about this project should be directed to Professor David Phillips at D.Phillips@exeter.ac.uk.

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Project team

Exeter – Professor Ronaldo Menezes
UQ – Associate Professor Dorina Pojani

Project description

Chrono-urbanism is an urban planning approach that prioritises time as a core resource, aiming to reduce travel time by placing essential services, leisure, and work within a short walk or bike ride. This approach seeks to create sustainable and healthy cities through “urban villages.” It provides the theoretical framework for concepts like the 15-minute city, which defines a 15-minute limit for a “short walk or bike ride.”  While this idea is appealing at first sight, it raises several problems.

1. The assumption that 15 minutes is an appropriate threshold across all contexts, populations, and types of amenities remains largely unexamined. Why 15, rather than 10, 20, or 30 minutes? 
2. The assumption that the health and wellbeing benefits of this model will be evenly distributed is largely untested. There is a risk that “urban villages” will be created mainly in areas with wealthier and healthier populations, leaving poorer and less healthy groups in “urban deserts” with limited access to amenities, active travel opportunities, and health-promoting environments.

This project will empirically test both assumptions to develop a more nuanced, evidence-based framework linking chrono-urban accessibility to health and socioeconomic outcomes. It will: 

1. Challenge the fixed-threshold paradigm by introducing the concept of the “N-minute city,” where N is a time variable that differs across socioeconomic contexts, amenity types (ranging from pharmacies and doctors’ surgeries to supermarkets and bus stops), and urban forms (e.g., low-rise versus high-rise). Amenity locations will be extracted from OpenStreetMap and validated against official datasets. A composite N will be computed as a weighted average across amenity types, with weights reflecting the relative necessity of each service (for example, a pharmacy is more essential at close proximity than a post office). The quality of amenities, not merely their presence, will be incorporated into the N measurement by drawing on open-access, crowd-sourced data such as online customer reviews. This work will produce a generalisable, open-source tool for computing variable-threshold accessibility indices.
2. Examine the relationships between N and health and socioeconomic outcomes, including self-reported health status, prevalence of chronic disease, mental wellbeing, physical activity levels, income, deprivation, educational attainment, vehicle ownership, and housing typology at fine spatial scales. The composite N will be further disaggregated by age, gender, and household composition to reveal how the health consequences of urban accessibility differ across population groups. This work will generate actionable insights for urban planners and public health practitioners seeking to improve population health and reduce spatial inequities in service provision.

The project involves six cities: London and Exeter in the UK, Brisbane and Melbourne in Australia, and São Paulo and Fortaleza in Brazil. These case studies cover diverse urban sizes, forms, wealth levels, and health profiles. The project uses spatial analysis and GIS, including network-based walkability modelling with OpenStreetMap, large-scale human mobility analysis with anonymised Call Detail Records and geolocated social media data, and computational techniques from network science and machine learning. It is interdisciplinary, combining theories of healthy and accessible cities with computational data science, network science, and spatial analytics.Contact

Questions about this project should be directed to Professor Ronaldo Menezes at R.Menezes@exeter.ac.uk.

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Project team

Exeter – Associate Professor Theo Economou
UQ – Associate Professor Nicholas Osborne

Project description

Temperature extremes and poor air quality are two of the main hazards humans are exposed to, particularly in urban environments where over 55% of population reside and rising. Although individually both temperature extremes (e.g. heat-stress) and air quality (e.g. Nitrogen Oxide from car fumes) are known to severely impact human health, it is unclear how these stressors interact although it is expected that their effect is compounded. The hazard to human health is therefore not well-understood, where individual assessments of either temperature or air quality are likely to underestimate the health risk. 

It is therefore not surprising that most health early warning systems are designed for either temperature extremes or air pollution but not their synergy. At the same time, there is a lack of a coherent and mathematically rigorous methodology for how health, environmental and population exposure and vulnerability data can be combined to optimally issue warnings in order to minimise health risk.

The aim for this project is to investigate the use of statistical AI methods for a) estimating the synergistic effect of temperature, humidity and air quality on human health (mortality and morbidity); b) to propose a prescriptive framework for using these estimates to optimally issue health warnings and c) to investigate the implications of climate change to the compound risk from environmental extremes.

The project will use state-of-the-art statistical AI approaches in environmental epidemiology (a unique strength of the Exeter-Queensland team), to quantify the degree to which the effects from temperature, humidity and air quality on human health are compounded, while also allowing for population characteristics (age, sex, socio-economic background) and exposure. The project will also use ideas from decision theory to investigate approaches for optimally issuing warnings with a view to minimise health risk to the respective sections of the population. Moreover, the project will utilise the latest data from climate models which contain information for how the climate, the population and its vulnerability/exposure are projected to change under various socio-economic scenarios. The information in these data sets and the estimated health risks as a function of environmental extremes will be combined to produce predictions of future health risk under different climate scenarios.

The project is expected to produce new knowledge into the synergistic effects of weather and air quality extremes, the way the estimates health risks might change in warming planet and present a health warning framework with which this knowledge can be used to mitigate health risk. The project partners, Public Health Scotland and the Met Office, will offer unique knowhow in terms of health surveillance, operational risk management and data access as well as insights regarding societal relevance and potential adoption and piloting of the resulting warning system.

Contact

Questions about this project should be directed to Associate Professor Theo Economou at T.Economou@exeter.ac.uk.

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Project team

Exeter – Dr Daniel Padfield
UQ – Associate Professor Jan Englenstaedter

Project description

Recent studies have shown that levels of antimicrobial resistance (AMR) increase at higher environmental temperatures, but we know very little about the mechanisms causing this correlational pattern. This project will use experiments, DNA sequencing, and mathematical modelling to increase our understanding of these mechanisms.

The key objective is to understand how temperature impacts the transfer rate and maintenance of plasmids in bacterial communities, which is one of the key ways that AMR spreads. Specifically, plasmid transfer should occur faster when bacteria have high growth rates and low mortality. As these microbial traits are temperature dependent, we should be able to predict plasmid transfer from the temperature response of the donor and recipient bacteria. Temperature will also change the selection for AMR. Being a plasmid-carrier can be costly in the absence of antibiotics, so the project will test how the costs and benefits of resistance traits change with temperature. If the strength of selection changes across temperatures, this may alter the rate at which bacteria evolve to overcome the costs of carrying the plasmids.

This project will take advantage of a library of Escherichia coli isolates, isolated from cattle, and a collection of plasmids that the isolates can take up. The plasmids have broad host ranges, high transfer rates, and have been found in different natural environments, making them relevant for spreading AMR in the environment. This set of isolates will be supplemented with several E. coli isolates that cause infections in humans allowing us to understand the conditions through which environmental E. coli may spread antibiotic resistance to pathogenic strains.

Below we suggest three different components of this project, but will encourage any PhD student to take ownership of the project to align it to their key interests.

Objectives  

1. Understand how plasmid transfer rate changes across temperatures in environmental and clinical bacteria.  
   
   Plasmid transfer rate is linked to the growth rates of the donor and recipient bacteria. We predict plasmid transfer across bacteria to be highest close to their optimal temperatures. 

• Understand how selection for resistance changes across temperatures. 
  
  We will quantify the cost of plasmid carriage and the impact of antibiotics on susceptible bacteria at different temperatures to quantify how the selection for resistance changes.
  
• Understand how plasmid spread and dynamics of bacteria change across temperatures in natural communities.  

We will use a range of methods (metagenomic sequencing, phenotypic assays, flow cytometry, qPCR) to measure how temperature affects plasmid carriage in simple and diverse communities.    

This interdisciplinary project will combine experiments, sequencing, and mathematical modelling to build and validate a mechanistic model linking temperature-dependent traits to AMR spread. Ultimately, these findings could inform mitigation strategies for AMR by informing risk prediction by identifying temperatures at which control measures targeting plasmids might be most effective and key antibiotics whose selection for resistance changes drastically across strains or temperatures.

Key references: 

[1] https://doi.org/10.1098/rspb.2019.1110   

[2] https://doi.org/10.64898/2025.12.03.692229

[3] https://doi.org/10.1128/msystems.00228-21

Contact

Questions about this project should be directed to Dr Daniel Padfield at D.Padfield@exeter.ac.uk.

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Project team

Exeter – Dr Jawad Fayaz
UQ – Professor Steven Kenway

Project description

Urban sewer and stormwater systems are increasingly stressed by climate change and rapid urbanisation. Intensifying rainfall, more frequent extreme events, and expanding impervious surfaces have increased sewer overflows that contaminate ecosystems, threaten public health, and breach environmental regulations. Infrastructure designed for historical rainfall regimes can no longer cope with the emerging “new normal”, where events once classified as rare now occur far more frequently. In England and Wales, sewer overflow impacts exceed £270 million annually and affect approximately 80,000 homes; in Australia, annual costs exceed AUD 982 million. These failures disproportionately affect vulnerable communities and require utilities to make timely, accountable intervention decisions under uncertainty.

Utilities must prioritise interventions such as pipe upgrades, storage expansion, real-time control, or maintenance under uncertain climate futures, constrained budgets, and regulatory obligations. Hydraulic simulators are physically detailed but computationally slow and calibration-intensive, limiting large-scale scenario exploration and optimisation. Purely data-driven approaches are faster but can produce opaque decisions and amplify inequities if trained on historically biased patterns or narrow objectives. There is therefore a clear methodological gap: the absence of a rapid, data-driven, physically informed and human-aligned decision framework capable of robust, equity-aware intervention planning under climate uncertainty.  

This PhD will develop a decision-support framework integrating physics-informed machine learning, scenario generation, and human-in-the-loop preference-based reinforcement learning to prioritise climate-robust and equity-aligned interventions. The core innovation is embedding expert judgement, regulatory constraints, and equity objectives directly into policy learning using structured preference feedback and explicit constraints.

The framework has three coupled components. First, a physics-informed graph surrogate model will emulate network hydraulics at scale, representing pipes and assets as a graph and predicting flows, depths, surcharge conditions, and overflow likelihood under rainfall and operational boundary conditions. Second, scenario generation will create climate and urban growth stress-tests by downscaling projections and integrating plausible land-use changes, with uncertainty explicitly represented to evaluate robustness rather than single-point forecasts. Third, a preference-learning reinforcement learning agent will propose intervention portfolios. Stakeholder preference rankings derived through inverse reinforcement learning and constraints related to compliance, safety, cost, and equity will guide policy learning, ensuring auditable and human-aligned decisions.

Deliverables include validated surrogate models for rapid risk evaluation, scenario libraries for stress-testing, a human-in-the-loop optimisation engine for invertion decisions with auditable decision logs, and reusable software modules suitable for utility integration.

Research objectives 

Build and validate physics-informed graph surrogate models for sewer network states and overflow outcomes. Develop climate and urban growth scenario generation with uncertainty. Implement preference-based reinforcement learning with explicit human and regulatory constraints. Evaluate policies on UK and Australian case studies using performance and equity metrics. 

Key research questions 

• How can stakeholder preferences and regulatory constraints be encoded to produce auditable, equity-aligned policies?
• How does climate and an uncertainty alter robust intervention prioritisation?
• What performance and equity gains are achievable relative to hydraulic-only and purely data-driven baselines?  

This project contributes directly to the Global Environmental Futures agenda by advancing methods for managing critical urban infrastructure under accelerating climate uncertainty while explicitly accounting for social and environmental equity. By delivering a validated, human-in-the-loop decision-support framework tested on real sewer networks in the UK and Australia, the research demonstrates how climate adaptation decisions can be made robust, transparent, and accountable rather than reactive or opaque. The resulting framework is designed to be transferable across regions and regulatory contexts, supporting long-term resiliency and sustainability of climate-adaptive cities under the Global Environmental Futures theme.

Contact

Questions about this project should be directed to Dr Jawad Fayaz at J.Fayaz@exeter.ac.uk.

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Project team

Exeter – Dr Elze Hesse
UQ – Professor Gary Schenk

Project description

The global transition toward a net-zero economy requires secure and sustainable supplies of critical minerals, with lithium forming the backbone of electric-vehicle batteries and grid-scale energy storage. Although most lithium is currently produced from brines, clay-hosted deposits represent one of the largest undeveloped global resources. However, existing extraction technologies for clays rely on high-temperature roasting followed by aggressive acid leaching, processes that are energy-intensive, generate substantial chemical waste, and produce significant carbon emissions. A further bottleneck is the “Mg/Li challenge”: the close chemical similarity between lithium and competing ions, particularly magnesium, severely limits the selectivity and efficiency of conventional extraction materials. Addressing these challenges requires fundamentally new approaches that integrate mineral liberation, molecular recognition, and process engineering.

This PhD project contributes to the development of a Bio-Integrated Liberation and Extraction (BILE) platform that combines electrochemical activation of lithium-bearing clays with biologically derived extraction systems. Within this broader collaborative framework, the candidate will lead the discovery, engineering, and deployment of lithium-binding proteins and peptides as highly selective biochelators for lithium recovery from complex leachates, while leveraging complementary expertise across the Universities of Exeter and Queensland and the Global Bioeconomy Alliance to integrate upstream liberation and downstream process development.

The central research objective is to identify and optimise biomolecular recognition systems capable of achieving Ångström-scale selectivity for lithium in the presence of high concentrations of competing ions. Using metagenomic sequencing of microbial communities from lithium-rich environments, including samples provided by industry partners (Cornish Lithium, Llamara), the student will mine environmental sequence datasets to discover novel metal-binding scaffolds. Promising candidates will be expressed, purified, and systematically characterised to determine affinity, selectivity, kinetics, and stability under relevant process conditions. Rational mutagenesis and computational protein design will then be applied to enhance lithium specificity and operational robustness in complex, high-impurity leachates.

In parallel, the candidate will develop immobilisation strategies that enable the deployment of optimised lithium-binding proteins and peptides in scalable extraction systems. Biomolecules will be incorporated into engineered matrices such as hydrogel-based biobeads or nanocellulose fibres to create reusable adsorption platforms suitable for continuous-flow operation. These systems will be evaluated in collaboration with process engineers (Adrian Oehmen, Nasim Amiralian, both UQ) to determine adsorption capacity, regeneration efficiency, and long-term stability, generating the performance data required for preliminary techno-economic assessment and integration into prototype direct-lithium-extraction workflows. The project will interface with complementary research on electrochemical clay activation (Bernardino Virdis, also UQ) to ensure that biomolecular capture technologies are compatible with upstream liberation processes.

By combining environmental microbiology, protein engineering, materials science, and process engineering, this research will establish a new class of biologically derived extraction materials that move beyond traditional inorganic sorbents. Expected outcomes include the discovery of previously uncharacterised lithium-binding biomolecules, quantitative insight into the molecular determinants of lithium selectivity, and validated immobilised systems suitable for pilot-scale testing. Collectively, these advances will contribute to the development of low-carbon, highly selective lithium extraction technologies and strengthen the capability of Australia and the UK in sustainable downstream mineral processing.  

Contact

Questions about this project should be directed to Dr Elze Hesse at E.Hesse@exeter.ac.uk.

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Project team

Exeter – Professor Gavin Tabor
UQ – Dr Sebastian Hoerning

Project description

Methane is a potent greenhouse gas with a global warming potential significantly greater than carbon dioxide over short time horizons. Accurate quantification of methane emissions from diffuse and complex sources—such as energy infrastructure, landfills, and urban environments—remains a major scientific and regulatory challenge. This is particularly important in environmental impact assessment for primary extractive industries; disused boreholes particularly from hydrocarbon prospecting are a major and unquantified source of methane emissions, as are the various processing plants involved in refining hydrocarbons. Emerging optical sensing technologies, including quantum gas LiDAR, offer the ability to detect methane concentrations remotely with unprecedented sensitivity and spatial coverage. However, translating such measurements into robust emission fluxes remains difficult due to atmospheric transport effects, complex flow environments, and significant uncertainty. 

This PhD project will develop an integrated framework combining computational fluid dynamics (CFD) with quantum gas LiDAR measurements to improve the quantification of methane emissions. The central research question is: how can physics-based flow modelling be coupled with advanced optical sensing to infer methane emission rates accurately and with quantified uncertainty?

The project will pursue three core objectives. First, it will develop high-fidelity CFD models of methane dispersion in representative environments, including idealised test cases and realistic geometries relevant to energy and environmental monitoring. These models will resolve the interaction between atmospheric flow, turbulence, and gas transport, providing a physically grounded description of plume evolution. Second, the project will integrate CFD predictions with quantum gas LiDAR measurements, using simulated and experimental data to relate observed concentration fields to underlying emission sources. This will include the development of inversion or data-assimilation approaches that exploit the totality of data from both measurement and modelling. Third, the project will quantify uncertainty arising from flow variability, measurement noise, and model assumptions, providing confidence bounds on inferred emission rates. 

Methodologically, the research will combine CFD simulations,  surrogate modelling, and inverse techniques to enable efficient interpretation of LiDAR data. The project will make use of high-performance computing facilities to support large-scale simulations and ensemble-based uncertainty quantification. A key innovation of the project is the use of LiDAR-derived spatial information to automate the construction of CFD simulation domains. Drawing on perception pipelines widely used in LiDAR-based autonomous systems such as self-driving cars, raw LiDAR data can be processed to identify and segment relevant objects (e.g. buildings, infrastructure, terrain) and convert them into simplified geometric representations suitable for CFD. This approach removes the need for manual geometry definition, enabling rapid and objective generation of flow domains directly from measurement data. 

The expected deliverables include:

1. validated CFD models of methane dispersion tailored to LiDAR-based sensing 
2. a coupled modelling–measurement framework for emission rate inference; and
3. quantitative assessment of uncertainty in methane emission estimates.

The project will contribute new knowledge at the interface of computational fluid dynamics, atmospheric sensing, and environmental monitoring, and will provide tools directly relevant to improving methane emission inventories and mitigation strategies.

Contact

Questions about this project should be directed to Professor Gavin Tabor at G.R.Tabor@exeter.ac.uk.

Apply now >>

Access scholarship funds for travel and development costs

UQ-homed UQ-Exeter Institute candidates can access a travel and development allowance of up to $18,000 over the duration of their program for expenses relating to travel between UQ and Exeter, and to support attendance at the annual UQ-Exeter Institute symposium and other workshops, short courses, and conferences. The allowance cannot be used for research equipment or consumables.  Research operating costs will be fully covered by the advisory team. Please use the Travel and Development allowance form to submit an application to access the funds.

For UQ-Exeter Institute candidates seeking advice on their travel allowance and who commenced prior to 2023, please contact us via graduateschool@uq.edu.au.

Stipend top-up during research stays at Exeter

Starting RQ1 2025, UQ-homed UQ-Exeter Institute PhD candidates conducting research in Exeter will receive a top-up to their stipend.  This will be paid in a lump sum and is based on the number of weeks spent at Exeter.  This additional funding aims to help cover the higher cost of living in the United Kingdom, and further support you as you progress in your research.  To align with the UQ-Exeter Institute joint PhD agreement, the stipend top-up is pre-approved for research stays at Exeter up to an accumulated total of 12 months. Payments beyond the pre-approved amount will require approval by the Dean of the UQ Graduate School.

Apply for your student visa

Before commencing your student visa application, please contact Exeter’s International Student Community & Support Team or book one of their online drop-in sessions. Visit Exeter’s Student Visas page for more information and webinars.

Visit GOV.UK for information on Student Visas and the UK Healthcare Surcharge.

Notify UQ of your travel

Once you have received your student visa (if applicable) and booked your travel to Exeter, complete the Joint PhD candidate – Notification of location Checkbox survey, ensuring that you upload evidence of your flight booking/details.  Please note that changing your status from ‘on-campus’ to ‘remote’ and providing evidence of your flight details is required before your top-up stipend can be awarded.

Notify UQ of your travel

Only submit after booking your travel

Notify now

Before you arrive, please reach out to Exeter’s PGR Support team to let them know when you will be arriving at Exeter.  The PGR Support team will direct you to your appropriate Faculty contact.  

Please read Exeter’s Before you arrive webpage for top tips you’ll need in preparation for your arrival in the UK.  This includes important information on the International Students Guide, visas, Healthcare, Living in the UK and much more.

Please remember to apply for an Exeter UniCard before you leave Australia.  Please submit your request so that your card is ready to collect when you arrive on campus.

General information for candidates travelling to Exeter can be found in Planning Your Travel to University and Airport Collection Service.

Living costs

Budgeting and managing living costs can be particularly challenging in a new country.  You can get an idea of what living costs in Exeter and Cornwall might include and tips on how to manage them. 

Accommodation

Read about the different student accommodation options, whether in Exeter, Cornwall or in the private sector in Exeter or Cornwall.

If you are planning on renting privately, please be mindful that leases are for a minimum period of 6 months.  When budgeting for the costs of accommodation during your research stays, it is recommended to plan your research stay for at least 6 months wherever possible.

If you are residing in University-managed accommodation, Exeter’s Residence Life Team is there to help you settle in, answer any questions and also run events.  To get an idea of their activities, visit their Res Life Instagram account.

Open a UK bank account

Please visit Exeter’s Bank accounts webpage for more information on opening a UK bank account.

Please read Exeter’s When you arrive webpage for a list of essential tasks for you to complete once you have arrived in the UK. 

Update your contact details

Please update your UQ mySI-net contact details with your UK address and telephone number.  You will be required to change these details back to your Australian address when returning to UQ.

Things to do – Getting around – Public transport

Devon and Cornwall are full of exciting events and activities all year round. Exeter campuses and the city centre are in comfortable walking distance, but taking the bus and cycling are also good options.  For longer routes, you’ll find train stations within walking distance of both Exeter campuses.

Once you have arrived in Exeter, you may be eligible to apply for a student discount (concession) on public transport fares.  Please see Stagecoach and National Rail for more information (note that mature aged students over the age of 25 may still be eligible for a 16-25 Railcard – see Railcards for Mature Students).

Exeter has three main campuses: Streatham Campus in Exeter, Devon, St Luke’s Campus in Exeter, Devon, and Penryn Campus near Falmouth, Cornwall.  Follow the links below for a campus map and information on travelling to campus:

• Streatham Campus, Exeter
• St Luke’s Campus, Exeter
• Penryn Campus, Cornwall

Exeter’s International student community and support offers a range of ways to get involved, such as the Intercultural Café, Day Trips, Global Chums, and more.

Here are some other helpful links for your time at Exeter.

• Student support
• Students’ Guild
• Student Sport
• Falmouth and Exeter Students’ Union (The SU)
• Your health and welfare
• Campuses and visitors
• Eat and Shop on campus
• Review the shopping and essentials services offered by Exeter, including Foodsave Community Fridge, offers and low-cost food options
• Visit Exeter’s Leisure and living webpage for information on transport, sport and free events
• Libraries and study spaces are open to students across campuses, offering online and in person services to make the most of library resources. The library liaison teams are available at library@exeter.ac.uk for those that are Exeter-based or library@fxplus.ac.uk for the Cornwall-based ones.

Please complete the Joint PhD candidate – Notification of location Checkbox survey to change your status back to onshore when you have returned to UQ.

Notify UQ of your travel

Only submit after booking your travel

Notify now

Update your contact details

Please update your UQ mySI-net contact details with your Australian address and telephone number.  

Pay your Student Services and Amenities Fee (SSAF)

UQ charges students the SSAF. This is a compulsory fee that the Australian Government requires universities to collect from students, to help provide student services, support and amenities for students.  For UQ-Exeter Institute students undertaking a research period at UQ, payment of SSAF will be required to remain actively enrolled.

Please note that if you are departing Exeter before the Research Quarter census date, UQ’s Student Services and Amenities Fees for that Research Quarter will apply.  Please log into your SI-net account to arrange payment of your SSAF by the due date.

Request a Confirmation of Enrolment

Exeter-based students will need to be issued with a Confirmation of Enrolment (COE) by UQ’s Graduate School before they can apply for an Australian student visa. 

To request a COE, Exeter-based students must follow the following process:

1. Student arranges their Overseas Student Health Cover (OSHC) through an approved OSHC provider
   • Exeter-based students are responsible for costs associated with OSHC, however, may be eligible to claim costs via their Exeter-funded Travel allowance.
2. Student emails OSHC certificate to UQ Graduate School (graduateschool@uq.edu.au), together with the details of their stay at UQ, i.e., arrival/departure date
3. Graduate School issues student with their COE for their visa application

Any requests to extend the existing COE must submitted via an Extend Studies And New CoE request online via my.UQ.

Apply for your student visa

As you are enrolled at UQ, you can access free migration and visa advice through the registered migration agent in UQ Union’s Student Advocacy and Support (SAS).  Please visit the Department of Home Affairs for more information on visas.

Notify UQ of your travel

Once you have received your student visa and booked your travel to Australia, complete the Joint PhD candidate – Notification of location Checkbox survey, ensuring that you upload evidence of your flight booking/details.

Notify UQ of your travel

Only submit after booking your travel

Notify now

Before you arrive, please reach out to the Higher Degree Research (HDR) Liaison Officer for your UQ School/Institute to let them know when you will be arriving at UQ. We recommend that you start your first visit with us within one month of the start of the Research Quarter.  You should register to attend the next available Graduate School HDR orientation session after you arrive. Please also review our Getting Started information to ensure you have completed any important steps to help you settle in to your PhD at UQ. 

Please read UQ’s Getting prepared to come to Australia webpage as this includes important information on arriving in Australia and much more.

Please remember to apply for a physical student ID card before you leave the UK.  Waiting times do apply, so please submit your request so that your card is ready to collect when you arrive on campus. 

General information and useful updates for international (and interstate) candidates arriving in Brisbane can be found on UQ’s International and Interstate Students webpage.   

If you’re arriving via the Brisbane Domestic or International Airports, there are several ways to travel from the airport, including:  

• Taxi
• Rideshare (Uber, Didi, Ola and Sheba)
• Airtrain 
• Con-x-ion shuttle bus. 

Check out the Brisbane Air Transport Options website for more.  Other useful resources include the Brisbane Airport International Arrival Guide and the Translink website (for public transport).

Candidates based at the Gatton campus

We suggest that you arrive and stay in Brisbane until the first weekday when we can book you a seat on the free St Lucia inter-campus shuttle bus to Gatton. Alternatively, if you arrive early on a weekday morning and can be at the St Lucia Campus by 7am, you can travel to Gatton on the shuttle on your day of arrival.  Please let us know your preference at least two weeks prior to arrival, so that we can help organise your trip to Gatton from the St Lucia Campus.

Accommodation

You can find information on both on-campus and off-campus accommodation options at UQ through UQ’s accommodation webpage. To assess the travel distance from campus you can use the Brisbane Translink website.

Updating your contact details

Please update your SI-net contact details with your Australian residential address and telephone number. It is a requirement for your student visa that you keep your contact details current with the university during your candidature.  You will be required to change these details back to your UK address when returning to the University of Exeter.

Opening an Australian bank account

Visit a local bank branch if you need a local bank account. Please note many banks offer accounts for international students with no withdrawal account fees.

There are numerous banks operating in Australia, with the four largest Australian banks being the Australian New Zealand (ANZ), Commonwealth Bank (CommBank), Westpac and National Australia Bank (NAB).

Pay your Student Services and Amenities Fee (SSAF)

UQ charges students the SSAF. This is a compulsory fee that the Australian Government requires universities to collect from students, to help provide student services, support and amenities for students. For UQ-Exeter Institute students undertaking a research period at UQ, payment of SSAF will be required to remain actively enrolled. Please log into your SI-net account to arrange payment of your SSAF by the due date.

Things to do – Getting around – Public transport

Brisbane is full of exciting events and activities all year round. To find your way around the city on public transport, use the Translink Journey Planner. We recommend buying a ‘go card’, an electronic ticket that allows you to travel on all Brisbane public transport services. Since COVID, many of the services are cashless, meaning the go card is required.

Once you have arrived and updated your semester address in si-net, you may be eligible to apply for a student discount (concession) on public transport fares.  Please see here for more information.

UQ has four campuses:

• Gatton – primarily focused on Agriculture, Food Sustainability, Environment, and Veterinary Science, located 87 kilometres west of Brisbane
• St Lucia – UQ’s main campus, located in inner west Brisbane
• Herston – home to Medicine and Public Health schools, the Oral Health Centre, UQ Centre for Clinical Research, Child Health Research Centre, and Herston Imaging Research Facility, located in inner north Brisbane
• Dutton Park – Across the river from St Lucia and is the primary teaching and research location for UQ’s School of Pharmacy and home to the Queensland Alliance for Environmental Health Sciences (QAEHS) and the Cornwall Street Medical Centre (UQ Health Care)

Here are some other helpful links for your time at UQ.

• Understand parking options at UQ
• Discover UQ maps for all your directions
• Establish safe habits on campus
• Explore UQ Sport services
• UQ Association of Postgraduate Students (APS)
• UQ Clubs and societies
• Review the food services offered by UQU, including Morning Marmalade & Kampus Kitchen (serving free meals to students across campuses) and Food Co-Op (free and low-cost groceries)

Our guide on preparing to leave UQ contains helpful information on who to advise of your departure dates, checking the status of any fee requirements, returning equipment and cleaning workspaces, etc. Please review those pages and advise your HDR Liaison Officer of your plans to return so we can ensure you are supported through this process.

Please note that if you are departing Australia after the Research Quarter census date, Student Services and Amenities Fees for that Research Quarter will apply.

Please complete the Joint PhD candidate – Notification of location Checkbox survey to change your status back to remote when you have returned to Exeter.

Notify UQ of your travel

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