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 seeking a Computational Postdoctoral Fellow to join the Bayraktar and Lotfollahi labs at the Wellcome Sanger Institute to apply cutting edge machine learning models to large-scale single cell and spatial transcriptomics datasets of neurodegenerative diseases. Supported by Open Targets, you will have access to novel cell atlassing datasets of patient tissue samples and close collaborators in biology and machine learning. This position is for a 3 year contract.
About Us:
The Bayraktar lab uses spatial and single cell transcriptomics to discover the biology of human brain disorders. The team has developed computational models for spatial transcriptomics data and generated large-scale multimodal atlases of human brain diseases. The Lotfollahi lab leverages AI and advanced experimental techniques to engineer cells and modulate their response to disease and perturbations. The team has a strong background in machine learning models for single cell and spatial transcriptomics.
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 the Role:
You will join a new project to create comparative cell atlases of Amyotrophic Lateral Sclerosis (ALS), Alzheimer's disease (AD) and Parkinson's disease (PD). You will work with a close group of wet and dry lab collaborators to analyse single nuclei and Xenium spatial transcriptomics datasets from brain tissue over 200 patients. You will use state-of-the-art machine learning models to integrate multi-modal data, identify disease vulnerable cell types and pathological cell interactions, with a focus on spatial data analysis.
This project is part of a broader programme of work also including cellular screening led by Andrew Bassett's team and collaborators across Oxford, Cambridge and London, and forms part of the Open Targets collaboration between academic and industrial partners to identify new drug targets for the treatment of neurodegenerative disease.
Relevant Publications:
- Kleshchevnikov, V. et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nat Biotechnol 40, 661-671 (2022).
- De Jong, G. et al. A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity. bioRxiv 2025.05.13.653495 (2025).
- Saraswat, M. et al. Decoding Plasticity Regulators and Transition Trajectories in Glioblastoma with Single-cell Multiomics. bioRxiv 2025.05.13.653733 (2025).
- Lotfollahi, M. et al. Mapping single-cell data to reference atlases by transfer learning. Nat Biotechnol 40, 121-130 (2022).
- Birk, S. et al. Quantitative characterization of cell niches in spatially resolved omics data. Nat Genet 57, 897-909 (2025).
About You:
We are seeking researchers with experience in computational biology and the ability to collaborate across departments to deliver projects. You will be a part of our Postdoctoral Fellow Programme, with opportunities to attend training courses, talks and networking events.
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
- Ability to analyse and interpret data with strong quantitative/computational skills
- Programming and bioinformatics skills
- Strong background in single cell, spatial transcriptomics or image analysis
- Experience using advanced statistical techniques, machine learning, and modern deep learning techniques
- Strong 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 reviews
- 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 organisational and problem-solving skills
Other information:
Salary per annum:(dependent upon skills and experience): £38,000-£49,156
Application Process:
Please apply with your CV and a Cover letter outlining how you meet the criteria set out above.
Closing Date: 27th July 2025
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 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.
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.
