PhD: Predictive Wildlife Metagenomics & Transmission ML

University of Exeter; Exeter; On-site; GBP 20,000 - 24,000; Full time

Benefits offered by this job

Funding for fees

Stipend £21,805 per annum

Job summary

The University of Exeter invites applications for an interdisciplinary PhD project that combines environmental and host-associated metagenomic data with state-of-the-art machine learning to identify patterns of pathogen transmission in wildlife populations, including migratory birds and badgers.

By integrating genomic, ecological, and environmental datasets, the project will develop predictive models to detect transmission hotspots, identify environmental reservoirs, and forecast pathogen spread

Qualifications

• Experience with metagenomic sequencing and microbiome analysis.
• Proficiency in applying machine learning to biological data.
• Ability to develop and validate predictive models for pathogen transmission.

Responsibilities

• Characterise microbial and pathogen diversity in wildlife and environmental samples.
• Identify transmission pathways and ecological drivers through data integration.
• Develop ML pipelines for preprocessing, feature engineering and model selection.

Skills

Metagenomics

Machine learning

Random Forests

Neural networks

Tools

MOFA

Network analysis

Job description

The University of Exeter invites applications for an interdisciplinary PhD project that combines environmental and host-associated metagenomic data with state-of-the-art machine learning to identify patterns of pathogen transmission in wildlife populations, including migratory birds and badgers.

By integrating genomic, ecological, and environmental datasets, the project will develop predictive models to detect transmission hotspots, identify environmental reservoirs, and forecast pathogen spread