Postdoctoral Fellow- Computational Biology and Machine Learning

Wellcome Sanger Institute
Location
Hinxton, UK
Job Type
Full-time
Posted
May 21, 2026
Views
38
Salary Range
$39k - $50k GBP

Job Description

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 Postdoctoral Fellow/Senior Postdoctoral Fellow to join our interdisciplinary team at the forefront of computational biology and AI for a 3 year fixed term 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 applicants 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, modelling cellular perturbation responses, predicting patient behaviours, and analysing multi-modal biological data.

Available Research Focus Areas

  • Spatial & Multi-omics Atlas Construction (MRC funded project)

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.

  • 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—including advanced generative modelling, scalable training algorithms, representation learning, and uncertainty modelling—tailored for biological data.

  • Multimodal Learning (Imaging + Genomics + Clinical Data) - MRC funded project

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

About Us

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

Akbar Nejat et al., Mapping and reprogramming human tissue microenvironments with MintFlow (bioRxiv, 2025)

Birk et al., Quantitative characterization of cell niches in spatially resolved omics data, Nature Genetics (2025)

Jeong et al., SIGMMA: Hierarchical Graph-Based Multi-Scale Multi-modal Contrastive Alignment of Histopathology Image and Spatial Transcriptome (arXiv, 2025)

Sanian et al., 3D-Guided Scalable Flow Matching for Generating Volumetric Tissue Spatial Transcriptomics from Serial Histology (arXiv, 2025)

What We Offer

Access to unique in-house datasets and world-class computational infrastructure

Opportunities to co-lead publications and present at ML and genomics conferences

Collaborative and inclusive environment with strong mentorship culture

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 Postdoctoral Fellow/Senior Postdoctoral Fellow to join our interdisciplinary team at the forefront of computational biology and AI for a 3 year fixed term 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 applicants 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, modelling cellular perturbation responses, predicting patient behaviours, and analysing multi-modal biological data.

Available Research Focus Areas

  • Spatial & Multi-omics Atlas Construction (MRC funded project)

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.

  • 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—including advanced generative modelling, scalable training algorithms, representation learning, and uncertainty modelling—tailored for biological data.

  • Multimodal Learning (Imaging + Genomics + Clinical Data) - MRC funded project

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

About Us

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

Akbar Nejat et al., Mapping and reprogramming human tissue microenvironments with MintFlow (bioRxiv, 2025)

Birk et al., Quantitative characterization of cell niches in spatially resolved omics data, Nature Genetics (2025)

Jeong et al., SIGMMA: Hierarchical Graph-Based Multi-Scale Multi-modal Contrastive Alignment of Histopathology Image and Spatial Transcriptome (arXiv, 2025)

Sanian et al., 3D-Guided Scalable Flow Matching for Generating Volumetric Tissue Spatial Transcriptomics from Serial Histology (arXiv, 2025)

What We Offer

Access to unique in-house datasets and world-class computational infrastructure

Opportunities to co-lead publications and present at ML and genomics conferences

Collaborative and inclusive environment with strong mentorship culture

Access to internal training, workshops, and career development resources through our Postdoctoral Fellow Programme.

About You

We are looking for enthusiastic researchers with a strong computational or quantitative background.

Essential Skills

PhD in relevant subject area, or on track to be awarded your PhD within 6 months of starting the role

Proven ability to deliver research projects

A track record of demonstrating research excellence and expertise in your area of research

Experience in advanced statistical techniques, machine learning and modern deep learning techniques

Experience with single-cell omics, spatial transcriptomics, or large-scale biological data integration

Knowledge of Python, including core-data science libraries such as Sci-Kit-Learn, SciPy, TensorFlow and PyTorch

Knowledge of software development good practices and collaboration tools, including git-based version control, python package management and code

Proven ability to develop and maintain effective working relationships with wide range of persons of differing level, abilities and knowledge

Foster an inclusive culture where all can thrive and diversity is celebrated

Team player with the ability to work with others in a collegiate and collaborative environment

Ability to effectively communicate ideas and results and present orally to groups

Commitment to personal development and updating of knowledge and skills

Ability to priortise, multi-task and work independently

Detailed orientated, strong organizational and problem-solving skills

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

Other Information

For further details, please see role profiles for Postdoctoral Fellow and for Senior Postdoctoral Fellow.

Salary per annum (dependent upon skills and experience):

Postdoctoral Fellow - £38,570-£49,893

Senior Postdoctoral Fellow - £44,305 - £49,893

Application Process

Please submit your CV and a cover letter detailing your research experience, interest in the focus area(s), and future aspirations.

Closing Date: 26th May 2026

Hybrid Working at Wellcome Sanger

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, Gender Equity 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 believe people do their best work when they can be their authentic selves. 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.

Our Benefits

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.  The Technician Commitment aims to empower and ensure visibility, recognition, career development and sustainability for technicians working in higher education and research, across all disciplines.

Frequently Asked Questions

Where is this job located, and is it remote, hybrid, or on-site?
This position is located in Hinxton, UK, and it offers hybrid working possibilities that depend on the role and team requirements.
What is the salary range for this position?
The salary for the Postdoctoral Fellow role is £38,570-£49,893 per annum, while the Senior Postdoctoral Fellow role pays £44,305 - £49,893, dependent on skills and experience.
What are the key qualifications for this role?
You'll need a PhD in a relevant subject area (or be on track to complete it within 6 months), experience in statistical techniques, machine learning, and knowledge of Python libraries. Experience with single-cell omics is desired.
What should I submit with my application?
Please submit a CV and a cover letter detailing your research experience, your interest in the focus area(s), and your future aspirations.
What is the deadline to apply?
The closing date for applications is May 26th, 2026.
What are some of the benefits offered?
The Sanger Institute offers access to in-house datasets, career development resources, a collaborative environment, and an employee wellbeing strategy.

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Job Information

Source: manual
AI Relevance: 95/100 (Highly relevant)
Remote Type: onsite
Experience: Mid
Allowed Locations: Worldwide
Skills & Tags:
AI machine learning deep learning genomics computational biology postdoc single-cell transcriptomics

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