(Senior) Computational Biologist / Computational Genomics Scientist

(Senior) Computational Biologist / Computational Genomics Scientist

Oxford, UK | On-site 3/4 days per week

AI | Genomics | Computational Biology | Diagnostics | Machine Learning

I’m currently supporting a major new interdisciplinary biology and technology initiative in Oxford focused on applying computational biology, AI, genomics, and advanced software engineering to real-world diagnostic and public health challenges.

This is a genuinely high-impact opportunity for computational biologists who enjoy solving difficult scientific problems and want to work in an environment where advanced biology, AI, software engineering, and translational science all come together under one roof.

Importantly, this is not a traditional “pipeline support” bioinformatics role.

The team is looking for scientists who can think critically about biological questions, develop novel computational methods, and contribute directly to the development of next-generation technologies and diagnostics.

The work includes:

• Developing computational approaches for microbial and metagenomic sequencing data

• Designing algorithms for genome assembly, binning, annotation, and functional characterisation

• Applying AI/ML and statistical modelling techniques to large-scale biological datasets

• Building scalable, reproducible workflows alongside software and engineering teams

• Collaborating closely with computational scientists, software engineers, and experimental biology teams

The team is looking for scientists who can think critically about biological questions, develop novel computational approaches, and contribute directly to next-generation diagnostic and public health technologies.

The organisation itself is focused on tackling major global challenges across:

• Human health

• AI and advanced computing

• Climate and sustainability

• Food security

Within the Generative Biology Institute, the focus is on applying advanced computational genomics, machine learning, and scalable infrastructure to accelerate biological discovery and diagnostic development.

The role will involve:

• Developing computational methods for analysing microbial and metagenomic sequencing datasets

• Designing algorithms for genome assembly, binning, annotation, and functional characterisation

• Applying AI/ML and statistical modelling approaches to complex biological data

• Building scalable and reproducible workflows alongside software and engineering teams

• Working closely with wet-lab scientists and interdisciplinary research groups

• Contributing to technically challenging projects with real translational impact

The environment is highly collaborative, technically strong, and heavily research-driven, but with a very applied mindset focused on real-world implementation rather than purely academic output.

Backgrounds of interest include:

• Computational Biology

• Computational Genomics

• Bioinformatics

• Machine Learning applied to biological data

• Microbial genomics / metagenomics

• NGS method development

• AI-driven biology

• 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

The role could suit:

• strong postdoctoral researchers looking for a more applied environment

• industry computational biologists wanting greater technical ownership

• method-development focused scientists who enjoy building new approaches rather than purely running existing workflows

Sponsorship and relocation support can be considered