Postdoctoral Fellow/Senior Postdoctoral Fellow

Wellcome Sanger Institute; Hartford; Hybrid; GBP 38,000 - 50,000; Full time

Job summary

A leading research institute in England is seeking a Postdoctoral Fellow/Senior Postdoctoral Fellow to advance research in computational biology. You will work on next-generation models integrating single-cell genomics, spatial transcriptomics, and generative AI. Ideal candidates should have a PhD in a relevant field, strong Python skills, and experience with machine learning techniques. The position offers a hybrid working model and competitive salary ranges from £38,000 to £49,156, depending on the role and experience level.

Benefits

Employee wellbeing programme

Hybrid working arrangements

Career development initiatives

Qualifications

• PhD required or on track to be awarded within 6 months.
• Experience with large-scale biological data integration.
• Strong organizational and problem-solving skills.

Responsibilities

• Build large-scale spatial and single-cell atlases.
• Develop AI models to predict cell fate and drug responses.
• Collaborate with internal and external stakeholders.

Skills

Machine learning

Statistical techniques

Team collaboration

Python programming

Single-cell omics

Education

PhD in relevant subject area

Tools

Python libraries (scikit-learn, SciPy, TensorFlow, PyTorch)

Version control (git)

Job description

Overview

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 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 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, generalisable deep models across public and internal datasets to support the Human Cell Atlas and broad Sanger research programmes.
• 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: Develop 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 undertaken in collaboration with Roser Vento‑Tormo at the Sanger Institute.
• The Open Targets (OT) research programme: Generate and analyse data to connect targets to diseases, assess evidence, and help identify and prioritise targets for drug discovery, including causal links and fundamental data.

About Us

We are 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 programmes, and international leaders in the field.

Benefits

We deliver a campus‑wide employee wellbeing strategy and programme, recognising the importance of health, lifestyle, and stress reduction. We are a signatory of the International Technician Commitment initiative (March 2018), which empowers and ensures visibility, recognition, career development, and sustainability for technicians in research and higher education.

About You

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

Essential Skills

• PhD in a relevant subject area, or on track to be awarded a PhD within 6 months of starting the role.
• Proven ability to deliver research projects.
• 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 scikit‑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 a 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 prioritise, multi‑task and work independently.
• Detail oriented, strong organisational 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 techniques, machine learning and modern deep learning techniques.
• Proven ability to work independently and deliver research projects.
• 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.

Salary Per Annum

Postdoctoral Fellow – £38,000–£49,156

Senior Postdoctoral Fellow – £43,650–£49,156

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: 1st February 2026

Hybrid Working

We recognise that hybrid working enhances work‑life balance and facilitates collaboration. The arrangement will vary by role and team.

Equality, Diversity and Inclusion

We aim to attract, recruit, retain and develop talent from the widest possible talent pool, creating an inclusive culture where everyone can thrive.