AI and Ecology PhD: Tracing Pathogen Transmission Between Wildlife and the Environment

AI and Ecology PhD: Tracing Pathogen Transmission Between Wildlife and the Environment

Research checked: 3 November 2026

Quick Decision

This One Health PhD links metagenomic profiles from wildlife and environmental samples with host movement, habitat and environmental conditions, then uses machine-learning and network methods to estimate pathogen occurrence, persistence and spread. Named approaches include Random Forests, Gradient Boosting Machines, deep neural networks and MOFA. The project is most relevant to applicants with the specified quantitative Master’s background and an interest in wildlife disease ecology. Sample coverage, confirmation of pathogen activity and validation across sites or seasons remain key design questions.

Research Problem and Doctoral Work

What Is Unsolved and Why It Matters

Pathogens can circulate between wildlife hosts and the environments they use, but the pathways and conditions that sustain transmission are often difficult to observe directly. The project proposes to combine metagenomic evidence with information on host traits, movement, habitat use, seasonality and environmental conditions. It asks whether this linked evidence can identify where a pathogen occurs, persists and spreads across landscapes, and which ecological factors are associated with those patterns.

The project is motivated by the need for better surveillance and targeted management, but metagenomic detection alone does not prove that a pathogen is viable, that a host is infectious, or that transmission moved in a particular direction. A covariance pattern or network edge is likewise a candidate pathway, not a demonstrated transmission event. The strength of the PhD will depend on matched sampling, appropriate negative controls, confirmatory assays and validation across time, space or host groups. The public project description does not yet specify these details.

Advertised Work, Methods and Scope

The official PDF sets out three connected objectives:

1. Characterise microbial and pathogen diversity. Use high-throughput metagenomic sequencing in model wildlife populations and their associated environments, including water, soil, sediment and foraging habitats.
2. Link microbiome patterns to ecology. Relate microbial community composition to host traits, movement behaviour, habitat use, seasonality and environmental conditions, and identify candidate ecological drivers of transmission.
3. Develop predictive analysis. Preprocess sequencing and environmental data, engineer features and select predictive models and informative features. The named approaches include Random Forests, Gradient Boosting Machines and deep neural networks for pathogen occurrence or transmission risk; MOFA to identify covariance across data types; and network analysis to identify putative pathways.

The intended targets include pathogen occurrence, persistence and landscape spread. Migratory birds and badgers are examples of wildlife systems in the description, not a complete or confirmed sample list. The project aims to produce knowledge that could inform surveillance, management and preparedness; those applications are potential downstream uses rather than guaranteed project outcomes. The PDF does not state pathogen groups, sample numbers, sites, sequencing platform, controls, diagnostic confirmation, data ownership or the planned train/test design. Official project PDF

Recent Research and Field Context

Recent work by the named team provides relevant ecological and methodological context:

• Harrison et al. (2026), badger faecal microbiome. In 165 samples from 72 European badgers collected over three years, social group and age were associated with microbiome variation; some microbial genera were associated with bovine tuberculosis infection probability, while repeated individuals showed varied microbiome trajectories. This is a close example of linking microbial observations with host and social context. It is observational and does not establish that microbiome differences cause infection or prove a transmission route. Molecular Ecology paper
• Prescott et al. (2025), helminth shedding in gamebirds. The study reports that co-infection, rather than infection intensity, was associated with increased shedding. It highlights the distinction between detecting infection and measuring a quantity closer to transmission potential, but concerns a different host–pathogen system. Ecology and Evolution paper
• Michels et al. (2025), disease risk after gamebird release. The paper examines zoonotic-risk associations and the challenge of separating spillback from correlated ecological drivers. It is relevant to cautious interpretation of One Health associations, but does not validate this project's proposed models or study system. Ecology Letters paper
• Ozsanlav-Harris et al. (2024), wildfowl movement. Biologging and disturbance records show that movement and behavioural responses differ between sympatric species. The study supports treating species and movement context as meaningful covariates; it does not measure pathogen transmission. Ecological Applications paper

The broader field increasingly combines pathogen genomics, movement and environmental surveillance. Recent examples include movement-driven transmission-network modelling, genomic and epidemiological analysis of HPAI-H5 across migratory flyways, environmental pathogen screening by nanopore sequencing and multi-host Usutu virus reservoir modelling. These studies support the value of combining data types, but their species, pathogens and study designs differ from this project. Their results should guide questions about sampling and validation, not be presented as outcomes the Exeter PhD will reproduce. A 2025 survey of 973 asymptomatic mammals also combined metagenomic and metatranscriptomic sequencing to map potential pathogen and antimicrobial-resistance sharing across wild and farmed hosts. It illustrates the breadth of such surveillance, but does not itself demonstrate active transmission. Cross-species mammal metagenomics study Movement-driven disease networks · HPAI-H5 migratory flyways · Environmental nanopore screening · Usutu virus reservoirs

School, Programme and Field Context

The official project PDF identifies the University of Exeter, the Centre for Ecology and Conservation (CEC) and the Stella Turk Building at Penryn Campus. The potential PhD route is Biological Sciences. Exeter describes the CEC as a research centre of more than 50 academics spanning whole-organism biology, disease, pathogens and parasites, movement ecology, molecular evolution, conservation and population biology. The university's Biological Sciences page summarises its REF 2021 result as placing the subject among the UK top 20 for world-leading research; this is a subject-level institutional signal, not a rating of this specific project. Biological Sciences PhD and research degrees · CEC disease research theme

The Biological Sciences route describes statistical programming, transferable skills, seminars and research training. It also describes an MPhil registration with a typical upgrade to PhD in the first year, followed by thesis submission and viva. The exact registration title and this studentship's training plan should be confirmed. CEC facilities include molecular-biology equipment such as qPCR and a DNA capillary sequencer, but the public facility list does not promise project-specific access or sequencing allocation. CEC academic staff

Supervisor and Lab Assessment

The project names Xav Harrison as lead, with Professor Stuart Bearhop, Associate Professor Barbara Tschirren and Dr Ruth Cox of the Animal and Plant Health Agency (APHA) as additional collaborators. Harrison's research centres on animal microbiomes, pathogens, host health and antimicrobial resistance; his current projects include badger microbiome/environment links and antimicrobial resistance in migratory birds. Bearhop contributes movement and foraging ecology, Tschirren disease and parasite ecology, and Cox applied wildlife disease work. This is a relevant spread of expertise for a project that needs to connect microbial data, host ecology and animal-health practice. The PDF does not assign day-to-day supervisory roles or confirm access to APHA-held samples, specific sites or facilities. XavLab · XavLab projects · Harrison CV · Ruth Cox profile

The recent papers above give direct examples of the supervisors' adjacent research. They show active work in microbiome variation, infection and shedding, ecological disease risk, and animal movement. They do not establish that the PhD will use the same data or field sites. Applicants should ask which supervisor leads the statistical pipeline, who directs field and laboratory sampling, how APHA will participate, and what training is available in metagenomics, pathogen confirmation, spatial analysis and model validation.

Research Direction and Career Context

This project sits at the intersection of wildlife disease ecology, molecular surveillance and predictive modelling. Recent field work shows why that combination matters: movement changes contact opportunities; environmental material may reveal exposure not visible from host sampling alone; and disease detections can be confounded by host age, social structure, season or land management. A practical thesis could compare host-only and host-plus-environment features, evaluate the contribution of movement or seasonal variables, or test whether candidate pathways replicate across sites. These are possible analytical angles, not promised work packages. Predictions should remain calibrated to their validation domain, and network analysis should be described as putative unless supported by direct transmission evidence.

Career pathways can include wildlife disease research, conservation and quantitative ecology, government animal-health surveillance, computational biology, bioinformatics and broader data-science roles. The UK's National Careers Service lists zoology and data science as distinct occupational routes; Skills England's 2026 assessment projects 66,000 additional priority-occupation jobs (44%) in life sciences by 2035, alongside replacement demand. These broad occupational estimates are not forecasts for wildlife-disease PhD vacancies or individual salaries. APHA is a relevant public-sector employer, but this project does not guarantee a placement or job outcome. Zoologist career profile · Data scientist career profile · Skills England life-sciences assessment · APHA recruitment information

Funding, Application and Living Cost

The 2027 EPSRC DLA competition is project-led. Its current call information describes full-time awards of up to 3.5 years, full tuition for successful eligible award holders, a £21,805 per-year stipend for 2026/27, and £5,000 total RTSG. The stipend is a living allowance; RTSG is research training and support money, not extra personal income. The 2027/28 stipend has not yet been published. The call states that successful international award holders at Exeter receive an institutional fee waiver to cover the international-fee difference, while international students may occupy up to 30% of the cohort. International eligibility therefore does not mean every international applicant will receive an award. Visa fees, the immigration health surcharge and moving costs are not covered. EPSRC DLA information

The central EPSRC DLA page lists the application deadline as 12:00 noon on Tuesday 8 December 2026 and requires references by 15 February 2027. The One Health PDF gives no separate reference deadline. The central-page overview expects interviews on 15–24 February 2027, but its application section still says interviews and outcomes are in 2026. Applicants should confirm the One Health project's application link and interview schedule before submission. The general DLA page sets the wider academic criteria; the project PDF adds the quantitative Master's condition. The programme's application materials include a personal statement, CV, transcript, two references and English-language evidence when required. Central EPSRC DLA application information · DLA general application information

Exeter estimates basic living expenses in Exeter or Cornwall at £1,300–£2,000 per month, based on average local spending in April 2026. The current stipend averages roughly £1,817 per month over twelve months, leaving an illustrative margin of about £517 at the low-cost end and a shortfall of about £183 at the high-cost end. Penryn accommodation examples for 2026/27 include a shared Glasney room at £149.66 per week, a single Glasney room at £199.50 per week, and a standard single at The Sidings at £196.81 per week. Availability and 2027/28 rates are not guaranteed. The government's Student visa maintenance figure of £1,171 per month outside London is an immigration evidence threshold, not a realistic living-cost estimate. Ask whether fieldwork, travel and accommodation away from Penryn are funded separately. Exeter budgeting estimate · Glasney accommodation · The Sidings accommodation · Student visa financial requirement

Applicant Fit and Preparation

Required Background and Skills

The project PDF specifies a Master's degree in a quantitative discipline, naming mathematics, computer science and statistics. The common EPSRC DLA guidance separately describes a First or Upper Second equivalent in an appropriate science or technology subject; some Lower Second applications may be considered alongside a relevant Master's or significant experience. Applicants should ask Exeter whether their exact degree title and modules satisfy both layers. The project PDF does not state that applicants must already know every named model or have fieldwork experience. Project PDF · EPSRC DLA eligibility and application

Preferred Experience and Suggested Preparation

The advertised methods make reproducible programming, data preprocessing, model evaluation and feature interpretation relevant preparation. Applicants may strengthen an application with a concrete example of quantitative modelling or data analysis, ideally showing how they handled missingness, class imbalance, temporal or spatial structure, or external validation. Familiarity with sequencing-derived features, ecology or animal health would help with biological interpretation, but the project-specific threshold is the quantitative Master's rather than a stated requirement to have mastered each tool. In particular, Random Forests, Gradient Boosting, deep neural networks, MOFA and network analysis are methods named for the doctoral work, not a separate checklist of mandatory entry skills.

Next Actions and Questions to Verify

Before Applying

1. Does the project require a completed quantitative Master's in one of the named subjects, and will the applicant's exact degree and module profile count as equivalent?
2. Can the supervisor confirm that the application is for the One Health title, provide the correct project-specific application link and confirm the noon 8 December deadline?
3. Which species, pathogen groups, environmental samples, sites and seasons are secured or planned, and what is the expected sample size?
4. Which samples and sequence data already exist, who controls them, and what confirmatory diagnostics or permissions are in place?

At Interview

1. How will sequencing detections be separated from contamination, transient DNA, viable infection, active shedding and actual transmission?
2. Which movement, habitat and seasonal data will be matched to each metagenomic sample, and how will temporal and spatial linkage be handled?
3. Which baselines, class-balance methods, train/test splits and external validation sites are planned for RF, GBM and deep-learning models?
4. How will MOFA and network analysis complement prediction, and what evidence would justify interpreting a pathway as more than an association?
5. What are the roles of the three Exeter supervisors and APHA partner, and how will quantitative, ecological and field components be supervised?

Before Accepting an Offer

1. Obtain written confirmation of the 3.5-year funded period, tuition coverage, international award eligibility, stipend rate and use of the £5,000 total RTSG.
2. Confirm formal Biological Sciences registration, the training plan, fieldwork and travel budget, APHA participation, data access and project milestones.
3. Check current Penryn accommodation costs and what visa, health surcharge, moving and fieldwork expenses must be paid from the stipend.

Evidence and Sources

Project, Programme and University

• One Health project PDF
• Exeter EPSRC DLA project directory
• EPSRC DLA funding and application guidance
• Biological Sciences PhD and research degrees
• CEC disease, pathogens and parasites research
• CEC academic and research staff

Supervisors, Lab and Related Papers

• Wild Microbiome Lab — Xav Harrison
• Current XavLab projects
• Xav Harrison CV and selected publications
• Ruth Cox profile, BADGER programme
• Badger faecal microbiome study (2026)
• Helminth co-infection and shedding (2025)
• Gamebird release and zoonotic disease risk (2025)
• Wildfowl movement and disturbance (2024)

Field Evidence and Methods

• Movement-driven disease transmission networks (2024)
• HPAI-H5 risk across migratory flyways (2026)
• Environmental pathogen screening with nanopore sequencing (2025)
• Multi-host Usutu virus reservoir modelling (2026)
• Cross-species mammal metagenomics study (2025)

Costs, Visa and Career Context

• Exeter living-cost budget
• The Sidings 2026/27 accommodation
• Glasney 2026/27 accommodation
• UK Student visa financial requirement
• Zoologist career profile
• Data scientist career profile
• Skills England life-sciences workforce assessment (2026)
• Animal and Plant Health Agency recruitment