Senior Scientist - Computational Method Development

Oxford, United Kingdom
Today
Seniority
Senior
Posted
17 Sep 2026 (Today)

Your new company
You'll be joining an innovative research team developing next-generation technologies at the intersection of genomics, artificial intelligence, and healthcare. You'll be part of a multidisciplinary department of computational scientists, bioinformaticians, engineers, and researchers applying advanced analytics to large-scale biological datasets and real-world scientific challenges.

Your new role
As a Senior Scientist, you will develop novel computational methods that transform complex sequencing data into actionable biological insights and support novel product development to have a real-world impact.
This is a genuine methods development role, focused on creating new algorithms and ML/AI approaches rather than applying existing bioinformatics pipelines.
The role is permanent and hybrid working - it requires some time on site (preferably 3 days/week but potentially flexible for the right candidate).
Key responsibilities include:

  • Designing and developing novel algorithms for genomics, sequencing, and large-scale biological data analysis
  • Building and evaluating machine learning models to address complex scientific and translational research questions
  • Validating and benchmarking new computational methods using large public and proprietary datasets
  • Working closely with bioinformaticians and software engineers to deploy methods within scalable, reproducible workflows
  • Collaborating across computational, biological, and data science teams to translate research into practical applications
  • Taking ownership of scientific projects from concept through implementation, evaluation, and delivery


There is the potential to take on some people leadership with this role, but the position can equally stay as a high-level technical expert.

What you'll need to succeed A successful candidate will combine strong quantitative skills with genuine experience developing new computational methods.You should have:

  • A PhD (or equivalent experience) in Computational Biology, Computer Science, Mathematics, Statistics, Physics, Machine Learning, Bioinformatics, or a related quantitative discipline
  • Proven experience developing novel algorithms, computational methods, or machine learning models, preferably within genomics or other large-scale biological data domains
  • Strong understanding of data structures, algorithms, statistical modelling, and quantitative problem-solving
  • Excellent programming skills in Python, with experience in other languages an advantage (eg C, C++, Julia, R, Rust, etc)
  • Experience owning projects and delivering computational tools, models, or analytical methods from development through validation
  • Experience with sequencing data, cloud computing, workflow development, ML Ops, or large-scale data infrastructure would be advantageous
  • The ability to independently lead projects and drive scientific direction with minimal supervision


What you'll get in return
As well as a highly competitive salary and package, plus bonus, you'll have the chance to make a significant real-world impact in the field of genomics.
You'll be working with highly capable and collaborative scientists and have access to significant compute resource.
There's also significant flexibility around working styles and patterns and good opportunities for career progression and development.

What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
If this job isn't quite right for you but you are looking for a new position, please contact us for a confidential discussion on your career.

Keywords: Computational, Genomics, Scientist, Research, Algorithm, Development, ML, Machine, Learning, AI, Bioinformatics, Statistics, Python, Maths, Sequencing, Modelling, Analytics, Computational, Software, Data, Biology, Quantitative, Programming, Cloud, Innovation, Biotechnology, Research, NGS, Pathogen, Bacteria, Virus, Disease, Oncology

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