Post Doctoral Research Associate in AI-driven Genomics for Rumen Microbiome

at  University of Lincoln

SCHOOL OF ENGINEERING & PHYSICAL SCIENCES

Location: Lincoln
Salary: From £37,999 pro rata
Please note, this post is fixed-term until 31 March 2026 and part-time at 0.5 FTE.
Closing Date: Tuesday 11 February 2025
Interview Date: Monday 24 February 2025
Reference: CHS190
The University of Lincoln is seeking a talented and motivated Postdoctoral Research Associate (PDRA) to join an interdisciplinary project focused on advancing genome assembly of rumen microbial species using semi-supervised machine learning (ML) techniques.
Rumen microbes play a vital role in breaking down plant material in cows and sheep while significantly influencing methane emissions—a potent greenhouse gas. Many low-abundance microbial species remain uncultured and poorly understood due to challenges in genome reconstruction. This project aims to develop and apply innovative ML models to overcome these challenges, contributing to sustainable agriculture and climate change mitigation.
In this role you will collaborate with experts in AI, genomics, and microbiology from the University of Lincoln and Queen’s University Belfast. The role includes developing and implementing semi-supervised ML models, analysing genomic data, and contributing to high-impact research outputs and future grant applications.

Key Responsibilities:

• Conduct original research in ML-driven genomic analysis.
• Develop advanced ML models to improve genome assembly.
• Collaborate across institutions and disciplines to advance research.
• Publish high-quality research outputs and contribute to grant proposals.

Person Specification:

• PhD in artificial intelligence, machine learning, bioinformatics, or a related field (or near completion).
• Strong experience in building data-driven models; familiarity with genomic or biological data is desirable.
• Proficiency in programming (e.g., Python, TensorFlow, PyTorch) and data pipelines.
• Evidence of research outputs of international standing.

In support of our commitment to developing colleagues by providing opportunities for internal movement and promotion, applications for this opportunity will only be accepted from people who are currently employed by the University of Lincoln, our current students, and any currently engaged agency workers who have been with us for more than 12 weeks. We actively encourage applications from all colleagues across the University with the relevant skills and experience.
If you would like further information or an informal discussion about this exciting opportunity, please contact Dr Wenting Duan at wduan@lincoln.ac.uk

• Conduct original research in ML-driven genomic analysis.
• Develop advanced ML models to improve genome assembly.
• Collaborate across institutions and disciplines to advance research.
• Publish high-quality research outputs and contribute to grant proposals