This is a research-focused position for a computational biologist who uses genomics and transcriptomics to frame and investigate cell biology hypotheses.
The Vento Lab is looking for a Senior Bioinformatician / Computational Biologist to lead single-cell and spatial transcriptomic data analysis across multiple projects centred on immune cell biology, with a particular focus on how immune cells specialise and function in the context of human reproductive tissues and women's diseases. The successful candidate will bring deep expertise in single-cell transcriptomics (spanning the full analytical workflow from raw data processing through to biological interpretation) and will be expected to critically interrogate data at every step, resolving technical artefacts and biological confounders with rigour and independence, and incorporating pertinent emerging AI-driven approaches.
Equally important is a genuine engagement with the biology of the tissues under study. The post holder will work in an environment where biological questions drive computational decisions, and where analytical outputs are always interpreted and communicated in biological terms. The ideal candidate will either bring existing knowledge of immune cell biology and reproductive tissues, or demonstrate the curiosity and capacity to develop it quickly. The role also encompasses the analysis of CRISPR perturbation datasets; while prior CRISPR experience is not required, familiarity with the principles of CRISPR screening is desirable, and the post holder will be expected to develop the same depth of critical analytical rigour in this domain as they bring to single-cell transcriptomics.
The successful candidate will join a highly collaborative, interdisciplinary team with expertise in cutting-edge single-cell genomics, immunology and women's health. Our culture is grounded in open communication, scientific curiosity, and mutual support.
Key responsibilities
- Lead the analysis and interpretation of large-scale single-cell (scRNA-seq, snRNA-seq, spatial transcriptomics, multiomics), spatial transcriptomic and CRISPR datasets, with the ability to independently troubleshoot and resolve issues at any stage of the workflow, from sequence alignment and cell calling through to clustering, annotation and downstream biological inference.
- Apply deep knowledge of single-cell data characteristics (including technical artefacts, doublets, ambient RNA, batch effects, and cell type-specific QC challenges) to make principled, well-justified analytical decisions grounded in both computational and biological reasoning.
- Use molecular and cellular biology knowledge to design biologically informed analytical approaches, critically interpret results, and ensure that methodological decisions align with experimental design and research aims.
- Implement innovative and creative data analysis strategies beyond standard pipelines to address complex research challenges and explore new directions.
- Work collaboratively as an active intellectual partner within the Vento interdisciplinary team, participating in scientific discussions and collaborative problem-solving to ensure computational approaches align with experimental work.
- Communicate results clearly and in a timely manner to project leaders, collaborators and the wider scientific community, including through publications and presentations.
- Organise and keep track of developed code and generated data within the group.
- Take a full part in the general duties of the team, passing on skills and knowledge to other team members and visitors, and participating in wider Sanger Institute activities as appropriate.
About you
You are a researcher with deep experience in single-cell transcriptomics and a genuine interest in immune cell biology and tissue biology. You are motivated by the opportunity to advance our understanding of human immunology and reproductive biology, and to contribute to meaningful scientific discoveries. You have a strong track record of analysing and interpreting single-cell transcriptomic and genomic data across the full analytical workflow, and you are able to think critically and independently about complex data challenges, moving beyond standard solutions when the science demands it. You work with precision and rigour, and you are comfortable operating in an environment where biological questions define the agenda for computational work.
You are seeking a senior research role that integrates immune cell biology with cutting-edge single cell/CRIPR genomic and computational approaches. Collaboration is central to your work, and you value constructive dialogue, shared problem-solving, and meeting deadlines within a supportive team environment. You will be supported in your personal and professional development, and will have the opportunity to lead peer-reviewed publications in single-cell genomics.
Essential skills
- MSc or PhD in a relevant biological, computational or quantitative discipline (Bioinformatics, Computational Biology, Genetics, Biomedicine, Computer Science, or equivalent); or equivalent professional experience.
- Demonstrated, in-depth experience in single-cell transcriptomics spanning the full analytical workflow (from alignment and QC through integration, clustering, annotation and biological interpretation) with a solid understanding of the technical and biological sources of variability in single-cell data and the ability to distinguish genuine biological signal from analytical artefact.
- Strong grounding in molecular and cellular biology, with the ability to formulate biological questions, critically interpret transcriptomic results, and contextualise findings within experimental design.
- Ability to align computational work with the scientific priorities of the team, ensuring analytical efforts are focused on the questions that matter most and delivered in a timely and effective manner.
- Proficiency in Python and/or R, and experience working in Unix/HPC environments.
- Experience with single-cell analytical frameworks such as Scanpy, scverse, Seurat or equivalent.
- Track record of research productivity demonstrated through publications or equivalent industry outputs.
- Enthusiastic, proactive attitude and genuine desire to learn, including in biological domains where prior knowledge may be limited.
- Strong communication skills for efficient and productive interactions with interdisciplinary team members.
- Ability to organise workload, manage competing priorities, and deliver to deadlines.
- Demonstrates inclusivity and respect for all.
Other Information
Please upload your cover letter along with your current CV and complete our short application form to apply.
Closing date: 1st June 2026
Contract type: 2.5 years
Salary: In the region of £45,803 - £54,965
Relevant publications of the group are listed below (links to PubMed).