MRC Postdoctoral Research Scientist in Spatial Lineage Tracing and Single-Cell Multiomics (LMS 2953)
£42,694 plus London allowances £5,560 per annum*
Additional allowances comprises at £1,000 lump sum settlement allowance plus a yearly Training Allowance of £850 in the first year, paid in monthly instalments. The Training Allowance increases to £1,300 in year two, and £1,800 in the third year.
3 years fixed term | Full-time | Location: Hammersmith London
Closing Date: 25 October 2026
Overall purpose:
Understanding how chemicals in our environment cause disease has been constrained by a fundamental lack of tools. The Tissue Biology Group is building spatial single-cell genomics technologies and high-throughput screening platforms to reveal, cell by cell, how exposures remodel tissues and drive disease. To do this, the group develops new methods for single-cell spatial multiomics, for in vitro and in vivo screening, and for the computational analysis these data demand.
We are interested in reading the history recorded in individual cells by somatic mutations and DNA methylation states that accumulate as tissues evolve. These marks can reveal how tissues are built, maintained, and repaired, and how these processes change with age, exposure, and disease. We aim to develop a technology that builds upon the Slide-tags platform (Russell et al. 2024 Nature) and is capable of reading these histories out in single cells whilst maintaining their spatial context within the original tissue.
We are looking for a talented postdoctoral scientist to lead the group's work on resolving cell lineage in situ. The post holder will develop and apply methods that recover lineage information together with spatial coordinates, and will apply them to answer questions about clonal dynamics in human tissues. This is a method-development post with deliberately broad reach. Once these measurements are established, they can be applied to address questions in development, ageing, cancer, and environmental exposure, and there will be scope to pursue those applications through collaboration.
This is a mixed wet/dry laboratory post. The successful candidate will generate their own data at the bench and take primary responsibility for its analysis, with support from the group and from the LMS core facilities in genomics, flow cytometry, light microscopy, and scientific computing.
As a newly established group, we can offer real scope to shape the direction of the project, alongside structured mentoring. We care about the kind of lab we are, not just the science we do. We look for curiosity and creativity, we work collaboratively and with mutual respect, and we want everyone in the group to grow as scientists and as people, with mentorship at every level and active support for training. Members of the group will work with an extensive network of collaborators, be encouraged to present their work at international meetings, and to publish work that others can build on, with methods documented and shared.
Key skills:
Experience in molecular biology.
Experience in experimental genomics and/or computational analysis of high-throughput sequencing data, with demonstrable aptitude for both.
Programming in R and/or Python for the analysis of sequencing data.
Expertise in single-cell and/or spatial genomics library preparation is an advantage.
Experience in DNA methylation sequencing, including low-input or single-cell approaches, is an advantage.
Experience in microfluidics, droplet or capsule-based assay development is an advantage.
Experience in tissue handling, cryosectioning, immunofluorescence, and FACS is an advantage.
Knowledge of HPC environments is an advantage.
A record of accomplishments indicating the ability to develop new methods, and to analyse, visualise, and disseminate data produced by high-throughput sequencing.
Main Responsibilities:
To plan and carry out research in accordance with the project aims, taking initiative in its direction.
To develop, optimise, and benchmark new experimental and computational methods.
To generate, manage, and analyse large single-cell and spatial sequencing datasets.
To maintain a highly organised and accurate record of work, and to work reproducibly.
To prepare work for publication and to contribute to grant submissions.
To present at group meetings, journal clubs, seminars, and national and international meetings as necessary.
To collaborate closely with other members of the team, and with internal and external collaborators.
To co-supervise MSc and PhD students and to assist others when required.
To contribute to the smooth running of the Group's/Unit's laboratories and facilities with other scientists, clinicians, technicians, and students within the laboratories.
To comply with the Institute, College, Division, and Unit safety practices and to attend courses on safety when appropriate.
Any other duties as may be deemed reasonable by the Head of Group as well as the Head of Division.
Education / Qualifications / Training required (will be assessed from the application form):
Essential:
A PhD (or equivalent experience) in genomics, molecular biology, computational biology, bioengineering, or a closely related discipline.
Desirable:
A first-author publication, preprint, or manuscript in preparation for imminent submission.
Previous work experience required (will be assessed from application form and at interview):
Essential:
Evidence that the candidate can plan and carry out a research project.
Hands-on wet laboratory experience in molecular biology, and a willingness to generate data at the bench from the start of the post.
Experience in working with high-throughput sequencing data, either generating it, analysing it, or both.
Desirable:
Experience in single-cell or spatial genomics library preparation (for example 10x Genomics, Smart-seq3, PIP-seq, split-and-pool barcoding, BD Rhapsody, Curio Trekker, Curio Seeker, 10x Visium, or comparable platforms).
Experience in DNA methylation sequencing, including single-cell or low-input methods.
Experience in microfluidics, droplet or capsule-based assay development.
Experience in tissue handling, cryosectioning, immunofluorescence, and live cell imaging.
Experience in flow cytometry and FACS.
An interest in, and proven experience of, developing or implementing new techniques in the lab.
Evidence of actively contributing to or driving scientific collaborations.
Knowledge and experience (will be assessed from the application form and at the interview):
Essential:
Demonstrable strength in either experimental genomics or computational analysis of sequencing data, with clear evidence of aptitude and appetite for the other.
The ability to write and apply code in R and/or Python for the analysis of sequencing data, or clear evidence of the capacity to acquire this quickly.
Experience in planning and completing research projects, demonstrated through relevant publications and presentations.
Excellent written communication skills in English and the ability to write clearly for publication.
Desirable:
Knowledge of lineage tracing, clonal dynamics, or somatic mutation analysis.
Familiarity with HPC environments and reproducible analysis workflows (for example version control, workflow managers, containers).
Knowledge of databases and resources for DNA methylation and single-cell data.
Personal Skills / Behaviours / Qualities (will be assessed at the interview):
Essential:
The ability to conduct reproducible research.
The ability to conduct a detailed review of recent literature.
The ability to develop and apply new concepts.
A creative approach to problem-solving, and persistence when a method does not work first time.
A keen interest in learning new skills, across both wet and dry laboratory work.
Excellent verbal communication skills in English and the ability to deal with a wide range of people.
The ability to motivate others to produce a high standard of work.
The ability to organise own work with minimal supervision.
The ability to prioritise own work in response to deadlines.
Advanced computer skills, including word-processing, spreadsheets, and the internet.
A willingness to work as part of a team and to be open-minded and cooperative.
A flexible attitude towards work.
Discipline and regard for confidentiality and security at all times.
A willingness to undertake any necessary training for the role.
Additional information:
Applicants should submit a maximum two-page CV, a brief cover letter describing scientific interests and motivation for the post and names and contacts of two scientific references.
Please note that applications may be reviewed by both LMS and Imperial staff
