Do you want to help us improve human health and understand life on Earth? Make your mark by shaping the future to enable or deliver life-changing science to solve some of humanity’s greatest challenges.

We are hiring a Senior Data Scientist/Principal Data Scientist to join our interdisciplinary team at the forefront of computational biology and AI for a 2 year fixed term contract. You will contribute to (lead - principal data scientist) transformative projects that integrate single-cell genomics, spatial transcriptomics, and generative AI to build next-generation models for understanding tissue biology and cellular dynamics across organs such as the pancreas, kidney, skin, and liver.

Available 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 multiome data in collaboration with leading Sanger groups.
• 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 (new) 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—including advanced generative modelling, scalable training algorithms, representation learning, and uncertainty modelling—tailored for biological data.
• Multimodal Learning (Imaging + Genomics + Clinical Data) Create models that integrate histopathology imaging, spatial proteomics, single-cell genomics, and patient-level clinical data to learn unified biological and clinical representations
• Leap Project - We are interested in developing large-scale AI models to stratify patients using diverse multi-omics data, with a strong commitment to equity and inclusion, particularly in women’s health. This work is being undertaken in collaboration with Roser Vento-Tormo at the Sanger Institute

The Open Targets (OT) research programme generates and analyses data to connect targets to diseases, assess the strength of this evidence, and help identify and prioritise targets for drug discovery. This includes evidence that causally links targets and diseases, as well as foundational data that helps us understand biological processes and disease progression more deeply.