This role is for a Principal/Senior Data Scientist on a 2‑year contract, offering an annual salary of £44,905‑£63,815. It is located in a hybrid work environment in Hinxton, England, United Kingdom. Candidates should have expertise in machine learning, Python, and experience in computational biology or related fields.
About Us
We are hiring a Senior Data Scientist/Principal Data Scientist to join the interdisciplinary Lotfollahi Group at the Wellcome Sanger Institute. Our mission is to develop data‑driven and biologically grounded AI tools for decoding complex cellular systems. We collaborate closely with the Human Cell Atlas, Sanger’s single‑cell programs, and international leaders in the field.
Research Focus Areas
- Spatial & Multi‑omics Atlas Construction – Build large‑scale spatial and single‑cell atlases across diseased tissues (pancreas, kidney, skin, liver) using spatial transcriptomics, scRNA‑seq, and multi‑ome data.
- Generative AI for Cell Fate & Perturbations – Develop diffusion, flow‑matching, and transformer‑based generative models to predict cell fate, tissue remodelling, and drug or perturbation responses in silico.
- Foundational Models for Single‑Cell Biology – Train large, generalizable deep models across public and internal datasets to support the Human Cell Atlas and broad Sanger research programs.
- Open Targets Translational AI Projects – Apply foundational and multi‑omics models to real‑world challenges in drug discovery, target identification, and target safety in collaboration with major pharma partners.
- Agentic AI for Scientific Reasoning & Experiment Design – Develop AI agents capable of hypothesis generation, experiment planning, and multi‑step scientific workflows using reinforcement learning and tool‑use models.
- Core Machine Learning Research – Advance fundamental ML methods tailored for biological data, including advanced generative modelling, scalable training algorithms, representation learning, and uncertainty modelling.
- Multimodal Learning (Imaging + Genomics + Clinical Data) – Create models that integrate histopathology imaging, spatial proteomics, single‑cell genomics, and patient‑level clinical data.
Role Responsibilities
- Lead and manage transformative projects that integrate single‑cell genomics, spatial transcriptomics, and generative AI.
- Design, develop, and evaluate advanced ML models tailored to biological data.
- Translate complex scientific questions into computational solutions and present results to multidisciplinary teams.
- Provide scientific leadership in interdisciplinary research, supervising PhD students and postdoctoral fellows.
- Publish high‑impact papers and contribute to the open‑science community.
Essential Skills & Qualifications
- MSc and/or Ph.D. in a quantitative discipline (e.g., Computational Biology, Bioinformatics, Statistics, Physics, Computer Science).
- Proven experience in advanced statistical techniques, machine learning, and modern deep‑learning frameworks (PyTorch, TensorFlow, SciPy, Scikit‑Learn).
- Strong programming skills in Python and experience with software development best practices (git, code reviews, package management).
- Experience with cloud environments (Amazon AWS S3, EC2, etc.) and data‑management pipelines.
- Excellent communication skills, able to explain complex methods to non‑technical stakeholders.
- Ability to work in a fast‑changing environment, prioritize tasks, and deliver consistent results.
- Publications in peer‑reviewed journals or preprint archives on machine learning or its application to biology.
- Experience in supervising PhD students or postdocs and writing manuscripts for publication.
Application Process
Please submit your CV and a cover letter detailing your research experience, interest in the focus areas, and future aspirations. The application deadline is 8th February 2026.
Equality, Diversity and Inclusion
We are committed to creating an inclusive culture where everyone can thrive. We welcome applications from all backgrounds, and all decisions are made without discrimination.
Benefits
- Hybrid working arrangement with flexible working hours.
- Competitive salary and statutory benefits.
- Opportunities to publish and collaborate with leading researchers worldwide.
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