Reearch Fellow (Computational Microbial Genomics) TLNT1_NI in Belfast

The Creevey Research Group at Queen's University Belfast is seeking an experienced Research Fellow in computational genomics to join a funded interdisciplinary project. The project, conducted in collaboration with the University of Lincoln and University of Liverpool, focuses on developing pangenome-based computational approaches for the detection of artificially introduced genetic elements in bacteria. The post holder will take a leading role in large-scale bacterial genome data acquisition, quality control, annotation, and network-based comparative genomic analysis. These activities directly underpin the development and evaluation of machine learning models for genomic anomaly detection. The role is primarily bioinformatic and genomic in nature; experience in AI and machine learning is valued but not required. The successful candidate will be required to obtain UK security clearance prior to or shortly after commencement of employment. Any offer of employment will be conditional upon receipt of satisfactory clearance.

Essential Criteria:

• Have or about to obtain a PhD in computational biology or bioinformatics or a closely related discipline, with a strong emphasis on computational analysis.
• Extensive experience in handling and analysing large-scale genomic datasets, including data acquisition from public repositories, quality filtering, and assembly assessment.
• Demonstrated experience in genome annotation workflows, including tools for gene prediction, functional annotation, and ortholog or gene family assignment.
• Experience in pangenome analysis, including the construction of pangenomes and interpretation.
• Experience developing and applying network-based approaches to comparative genomic data.
• Advanced programming skills in Python, R, or other languages appropriate for large-scale biological data analysis, with experience working in Linux/Unix environments.
• Demonstrated experience designing and implementing reproducible bioinformatics pipelines.
• Experience working with high-performance computing environments and job schedulers (e.g., Slurm or equivalent).
• Experience with version control systems (e.g., Git) and reproducible research practices.
• Ability to communicate complex technical information clearly, both in writing and verbally, including to interdisciplinary audiences.
• Ability to work independently and as part of a multidisciplinary, multi-institutional team.
• Strong scientific writing skills, with a track record of, or demonstrable capacity for, peer-reviewed publication commensurate with career stage.
• Willingness to travel for collaborative activities with partner institutions.
• Willingness to obtain UK security clearance as a condition of employment and to work with sensitive data under appropriate data security protocols.

To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document on our website.