A Research Assistant / Research Associate position is available in the group of Prof. Walid T. Khaled at the Department of Pharmacology and Cambridge Stem Cell Institute, University of Cambridge.
This position is part of a major programme of work, focused on understanding and ultimately preventing hereditary breast cancer. Building on the Khaled Lab's expertise in tumour initiation and early transformation, this project aims to intercept breast cancer before it starts, with a particular focus on individuals carrying high-risk mutations in BRCA1, BRCA2 and PALB2. The team studies the early molecular and cellular changes that occur in high-risk breast tissue and seeks to map the spatiotemporal clonal dynamics that drive pre-malignant transformation. This role offers a rare opportunity to contribute to cancer interception science at the frontier of personalised prevention, with strong translational potential.
The role
Working closely with researchers across the team, you will:
- Analyse large single-cell RNA sequencing (scRNA-seq) datasets of the mammary gland, characterising cell states, differentiation trajectories and pre-malignant change across development, pregnancy, lactation and involution
- Integrate and harmonise scRNA-seq datasets across experiments, conditions and species, including mapping experimental data against established mouse and human breast cell atlases
- Design and apply lineage-tracing analyses, recovering and analysing heritable DNA barcodes (e.g. LARRY) directly from scRNA-seq data to reconstruct clonal histories of mammary epithelial cells
- Develop and maintain reproducible computational pipelines for quality control, clustering, annotation, differential expression and trajectory inference
- Integrate single-cell and spatial transcriptomic data to resolve epithelial-microenvironment interactions and tumour-permissive niches
- Work closely with wet-lab colleagues to interpret results, refine experimental design, and prepare figures and analyses for publications, reports and presentations
- Maintain meticulous, well-documented and version-controlled analysis records
Requirements:
Essential
- A BSc (Research Assistant) or PhD (Research Associate), or equivalent experience, in computational biology, bioinformatics, genomics, or a related quantitative discipline
- Demonstrable experience analysing large single-cell RNA sequencing datasets, ideally of the mammary gland or other epithelial tissues
- Hands-on experience integrating scRNA-seq datasets across samples, batches or studies, and mapping data onto reference atlases
- Experience with lineage tracing and the analysis of DNA barcodes recovered from scRNA-seq data
- Strong programming skills in R and/or Python, with standard single-cell toolkits
- Familiarity with breast cancer biology and models of hereditary breast cancer (BRCA1, BRCA2, PALB2)
- Meticulous record-keeping, strong organisation and the ability to prioritise across concurrent analyses
- An effective communicator and strong team player, able to work closely with experimental biologists
Desirable
- Experience developing reproducible, version-controlled analysis pipelines (e.g. Git, Snakemake, Nextflow)
- A track record of contributing to peer-reviewed publications
Fixed-term: The funds for this post are available for 6 months in the first instance, subject to a probation period and performance review.
Please ensure that you upload a covering letter highlighting relevant experience to this project. You will also need to upload a CV and include the names of two referees as part of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Informal enquiries are welcomed and should be directed to: Professor Walid Khaled, email: [email protected]
For enquiries about the online application process, please contact the HR Team, [email protected]
Please quote reference PL50034 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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