Job Description
Senior Scientist – Computational Biology / Machine Learning
Hybrid | Full Time
London, United Kingdom
Overview
We are seeking a Senior Computational Scientist to help translate advanced machine learning models into impactful, real-world discovery workflows.
In this role, you will provide scientific leadership across model evaluation and applied biological use cases, ensuring research remains grounded in the most relevant challenges in drug discovery and translational research.
This position sits within a growing computational biology team and reports into the Head of Computational Biology. You will join as a senior individual contributor, with the opportunity to take on management responsibilities as the team expands.
You will act as a key scientific partner to research teams, support and mentor junior scientists, and collaborate closely with product and commercial teams to translate cutting-edge biology and machine learning into solutions that deliver real value for customers.
Key Responsibilities
* Lead evaluation and application of machine learning models for biological discovery workflows
* Apply advanced ML methods to complex biological datasets, particularly single-cell and omics data
* Partner with research teams to translate model outputs into meaningful biological insights
* Collaborate with product and business teams to shape deliverables and real-world applications
* Mentor junior scientists and contribute to the growth of the computational biology function
* Operate in a fast-moving environment, iterating quickly from prototype to experiment to insight
Requirements
* PhD in Computational Biology, Machine Learning, Bioinformatics, or a related field with a focus on single-cell and machine learning, plus 2+ years industry experience, OR
* MSc in a relevant field with 5+ years industry experience applying machine learning to single-cell or omics datasets
* Strong understanding of machine learning approaches for biological data, including methods such as transformers, VAEs, diffusion models, and classical ML
* Hands-on experience using modern ML frameworks such as PyTorch (or similar)
* Strong communication skills with the ability to translate complex scientific concepts for both technical and non-technical audiences
* Comfortable working in fast-paced, iterative research environments
* Passion for working at the intersection of biology and machine learning