Senior Postdoctoral Fellow/Postdoctoral Fellow

Senior Postdoctoral Fellow/Postdoctoral Fellow

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 Postdoctoral Fellow/Senior Postdoctoral Fellow across experience levels to join our interdisciplinary team at the forefront of computational biology and AI for a 3 year postdoctoral Fellow contract. You will contribute to (lead- senior postdoctoral fellow) 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.

We welcome applications from diverse technical and scientific backgrounds — from those interested in fundamental questions in biology and medicine, to those focused on ML/AI method development. We are particularly excited to work with individuals who are passionate about biology, foundation model development, modeling cellular perturbation responses, predicting patient behaviors, and analyzing multi-modal biological data.

Available Research Focus Areas

1. Construction of Spatial and Multi-omic Atlases Across Diseased Tissues

Contribute to building comprehensive spatial and multi-modal atlases from diverse disease-affected human tissues using cutting-edge technologies such as spatial transcriptomics, single-cell RNA-seq, and multiome (RNA + ATAC) data. You will be involved in data integration and modeling across tissues like pancreas, kidney, skin, and liver, supporting atlas generation that informs both basic biology and translational research in tissue-specific disease contexts in collaboration with other groups such as Haniffa lab , Vento lab , Bayraktar lab .

2. Generative AI for Cell Fate and Perturbation Modeling

Develop novel generative models (e.g., diffusion, transformers, flow-matching) to model and predict cell fate transitions and tissue remodeling under various perturbations. This includes modeling drug responses, regeneration, inflammation, and other biological processes in silico.

3. Foundational Models for Single-Cell Biology

Join our foundational model team to build large-scale, generalizable deep learning models trained on extensive internal and public single-cell datasets. You will contribute to building models that can generalize across tissues, species, and conditions—powering the Human Cell Atlas and internal Sanger programs in health and disease.

4. Open Targets-Funded Projects

There are exciting opportunities to work on projects funded by Open Targets , where you will apply foundational model development and cutting-edge data analysis to real-world problems in drug discovery and target identification. These projects are conducted in close collaboration with leading pharmaceutical companies, bridging academic research and practical industry applications. This is a unique chance to gain experience in translational bioinformatics, building tools and models directly relevant to therapeutic development.

Open Targets is a public-private partnership involving the Wellcome Sanger Institute, a world-leading genomics institution, EMBL’s European Bioinformatics Institute (EMBL-EBI), a global leader in the management, integration and analysis of public domain life science data, and world-leading pharmaceutical companies GSK, Sanofi, MSD, Pfizer, and Genentech

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.

About You:

We are looking for enthusiastic researchers with a strong computational or quantitative background and experience in one or more of the following:

• PhD in Computational Biology, Biology, Bioinformatics, ML/AI, Genomics, Statistics, Physics, or a related quantitative field or to be on track to be awarded your PhD within 6 months of starting the role
• Skills Python, with experience using scientific and ML libraries (e.g., PyTorch, scikit-learn, NumPy, scanpy)
• Experience with single-cell omics, spatial transcriptomics, or large-scale biological data integration (data focused postdocs)
• Demonstrated experience in machine learning (method focused postdocs), preferably with generative or deep models.
• Proven ability to develop and maintain effective working relationships with wide range of persons of differing level, ability and knowledge
• Team player with the ability to work with others in a collegiate and collaborative environment
• Commitment to personal development and updating of knowledge and skills
• Ability to priortise, multi-task and work independently
• Detailed orientated, strong organisational and problem-solving skills
• Foster an inclusive culture where all can thrive and diversity is celebrated

Additional Skills for Senior Postdoctoral Fellow:

• Strong knowledge of Python, including core data science libraries such as Scikit-Learn, SciPy, Tensorflow and PyTorch
• Proven experience using advanced statistical statistical techniques, machine learning and modern deep learning techniques
• Proven ability to work independently and deliver research projects
• Relevant solid publication record in either machine learning or application of machine learning in biology
• Strong influencing skills to engage with internal and external stakeholders
• Critical and analytic thinking around problems
• Demonstrable good time management and project management skills

About the Group:

You will join the Lotfollahi Group , an interdisciplinary team of ML researchers, computational biologists, clinicians and experimentalists. 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.

Key Publications and References:

• Birk, S, et al. Quantitative characterization of cell niches in spatially resolved omics data. Nature Genetic (2025)
• Lotfollahi, M. et al. Mapping single-cell data to reference atlases by transfer learning. Nature Biotechnology (2021)
• Lotfollahi, M. et al. scGen predicts single-cell perturbation responses. Nature Methods (2019)
• Lotfollahi, M. et al. Biologically informed deep learning to query gene programs in single cell atlases. Nature Cell Biology (2023)

What We Offer:

• Access to unique in-house datasets and world-class computational infrastructure
• Opportunities to co-lead high-impact publications and present at top ML and genomics conferences
• Collaborative and inclusive environment with strong mentorship culture

Salary per annum (dependent upon skills and experience):

Application Process:

Please submit your CV and a cover letter detailing your research experience, interest in the focus area(s), and future aspirations and how you meet the criteria set out above.

Closing Date: 8th July 2025

We recognise that there are many benefits to Hybrid Working; including an improved work-life balance, with more focused time, as well as the ability to organise working time so that collaborative opportunities and team discussions are facilitated on campus. The hybrid working arrangement will vary for different roles and teams. The nature of your role and the type of work you do will determine if a hybrid working arrangement is possible.

Equality, Diversity and Inclusion:

We aim to attract, recruit, retain and develop talent from the widest possible talent pool, thereby gaining insight and access to different markets to generate a greater impact on the world. We have a supportive culture with the following staff networks, LGBTQ+, Parents and Carers, Disability and Race Equity to bring people together to share experiences, offer specific support and development opportunities and raise awareness. The networks are also a place for allies to provide support to others.

We want our people to be whoever they want to be because we believe people who bring their best selves to work, do their best work. That’s why we’re committed to creating a truly inclusive culture at Sanger Institute. We will consider all individuals without discrimination and are committed to creating an inclusive environment for all employees, where everyone can thrive.

We are proud to deliver an awarding campus-wide employee wellbeing strategy and programme. The importance of good health and adopting a healthier lifestyle and the commitment to reduce work-related stress is strongly acknowledged and recognised at Sanger Institute.

Sanger Institute became a signatory of the International Technician Commitment initiative In March 2018. TheTechnician Commitment aims to empower and ensure visibility, recognition, career development and sustainability for technicians working in higher education and research, across all disciplines.

Every year the Wellcome Sanger Institute supports the visits of dozens of overseas researchers from across the globe to the Genome campus to collaborate, share insights and to undertake ground-breaking scientific research. Our reliable in-house service provides expert advice and guidance to support current and prospective staff, and visitors at various points of their journey. We are able to provide guidance through your entire journey, from initial visa application through to extensions and applications of Indefinite Leave to Remain, the service is proud to support your personal applications and those of your dependants and family members.

Global Mobility and Immigration Service (16 kB)

Senior Postdoctoral Fellow/Postdoctoral Fellow

Wellcome Trust Genome Campus, Hinxton Saffron Walden, United Kingdom

Published

2025-06-17

2025-07-08 23:59 (Europe/London)
2025-07-09 00:59 (CET)

We are a world-leading genomics research institute. Our work helps improve human health and understand life on Earth.

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