Senior Bioinformatician

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.

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.

• 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.

• 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…