{ “@context”: “http://schema.org”, “@type”: “JobPosting”, “title”: “(Senior) Computational Biologist / Computational Genomics Scientist”, “description”: “
Overview
Senior Computational Biologist / Computational Genomics Scientist
Focused on applying computational biology, AI, genomics, and advanced software engineering to diagnostic and public health challenges in Oxford.
Responsibilities
- Develop computational approaches for microbial and metagenomic sequencing data.
- Design algorithms for genome assembly, binning, annotation, and functional characterisation.
- Apply AI/ML and statistical modelling techniques to large-scale biological datasets.
- Build scalable, reproducible workflows alongside software and engineering teams.
- Collaborate closely with computational scientists, software engineers, and experimental biology teams.
Backgrounds of Interest
- Computational Biology
- Computational Genomics
- Machine Learning applied to biological data
- Statistical Genomics
Key Requirements
- PhD (or equivalent experience) in Computational Biology, Bioinformatics, Computer Science, Genomics, or related field.
- Strong programming skills (Python essential, C/C++/Rust beneficial).
- Experience working with sequencing or genomic datasets.
- Strong grounding in algorithms, statistical modelling, or ML approaches.
- Scientific curiosity and strong problem‑solving ability.
Potential Candidates
- Strong postdoctoral researchers seeking a more applied environment.
- Industry computational biologists desiring greater technical ownership.
- Method-development scientists who enjoy building new approaches rather than running existing workflows.
Company: BioTalent
Location: Oxford
Job Description:
Overview
Senior Computational Biologist / Computational Genomics Scientist
Focused on applying computational biology, AI, genomics, and advanced software engineering to diagnostic and public health challenges in Oxford.
Responsibilities
- Develop computational approaches for microbial and metagenomic sequencing data.
- Design algorithms for genome assembly, binning, annotation, and functional characterisation.
- Apply AI/ML and statistical modelling techniques to large-scale biological datasets.
- Build scalable, reproducible workflows alongside software and engineering teams.
- Collaborate closely with computational scientists, software engineers, and experimental biology teams.
Backgrounds of Interest
- Computational Biology
- Computational Genomics
- Machine Learning applied to biological data
- Statistical Genomics
Key Requirements
- PhD (or equivalent experience) in Computational Biology, Bioinformatics, Computer Science, Genomics, or related field.
- Strong programming skills (Python essential, C/C++/Rust beneficial).
- Experience working with sequencing or genomic datasets.
- Strong grounding in algorithms, statistical modelling, or ML approaches.
- Scientific curiosity and strong problem‑solving ability.
Potential Candidates
- Strong postdoctoral researchers seeking a more applied environment.
- Industry computational biologists desiring greater technical ownership.
- Method-development scientists who enjoy building new approaches rather than running existing workflows.
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Posted: May 18th, 2026