Computational Biologist
Ellison Institute of Technology
Computational Biologist
Ellison Institute of Technology
Interdisciplinary R&D translating science into products
Ellison Institute of Technology · Oxford, United Kingdom (Hybrid) · Full-time · Posted 2026-10-09
Workplace: hybrid
Department: AI & Robotics
At the Ellison Institute of Technology (EIT), we’re on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, policy makers, and entrepreneurs to tackle humanity’s greatest challenges in four transformative areas:
This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas for lab to society. Explore more at www.eit.org
We’re looking for a Computational Biologist to work at the interface of microbiology and AI. The role requires being a subject matter expert within a team of AI researchers and engineers and the hands-on ability to work on projects including transforming complex biological sources into robust, high-quality data sets, building bioinformatics solutions, and designing evaluations for foundation models.
This role requires deep expertise in microbiology and bioinformatics methods, strong scientific judgement, and the ability to critically assess and improve how biological data is used in computational systems. You will work closely with AI Scientists and Engineers to ensure models are biologically sound and capture the most important signals.
Key Responsibilities
Structure, curate, and transform large-scale microbiology data for use in machine learning systems
Define biologically grounded tasks, representations, and evaluation frameworks aligned with real biological signal
Interrogate datasets, methods, and model outputs to identify bias, leakage, and invalid assumptions
Apply, adapt, and critically assess state-of-the-art bioinformatics methods in real-world settings
Build robust, reproducible Python workflows and collaborate closely with research and engineering teams
Essential Knowledge, Skills, and Experience
Extensive experience in genomics and computational biology, with strong understanding of methods such as genome assembly, alignment, and variant analysis
Experience working with large-scale genomics datasets including data preparation and modelling
Proven track record of solving complex computational biology problems, translating them into computational and statistical methods and delivering working implementations.
High proficiency in Python for data processing and modelling
Desirable Knowledge, Skills, and Experience (in rough order of desirability)
Background in software engineering
Experience with microbiology and prokaryotic biology
Experience with long- and short-read sequencing technologies
Experience with foundation models or representation learning applied to biological data
We offer the following salary and benefits:
Enhanced holiday pay
Pension
Life Assurance
Income Protection
Private Medical Insurance
Hospital Cash Plan
Therapy Services
Perk Box
Electric Car Scheme
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Why work for EIT:
At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!
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Interdisciplinary R&D translating science into products
The Ellison Institute of Technology unites science, engineering, policy, and entrepreneurship to tackle big global problems through four focus areas: Health, Medical Science & Generative Biology; Food Security & Sustainable Agriculture; Clean Energy Generation & Storage; and Artificial Intelligence & Robotics. It translates scientific discovery into commercial products and sustainable companies, reinvesting profits to fund more research; a key project is the GPAS bioinformatics platform for rapid pathogen analysis to help prevent pandemics. The institute differentiates itself through a deep alliance with the University of Oxford, an alliance faculty model that allows researchers to work across both institutions, and patient capital commitments to fund high-risk, high-reward research. Its goal is to solve global challenges by turning scientific breakthroughs into market-ready solutions and sustainable enterprises.
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