Computational Biologist - Cell Ontology & Agentic AI Workflows

External

Sanger · Hinxton, Cambridgeshire

Full-timeHybridToday

Machine LearningNeo4jNLPPython

Cover Letter Connect

Prepare for this interview

Elite

AI-generated questions, company research, and talking points tailored to this role

About the role

The Cellular Semantics team develops and maintains the Cell Ontology and associated knowledge infrastructure. We are a small, technically ambitious team that punches well above its weight, our ontology is used by every major single-cell atlas project and platform worldwide. We are funded by the Allen Institute (BICAN/HMBA) and the Chan Zuckerberg Initiative. We are currently investing heavily in agentic AI approaches to scale our work. Our tools include custom Python packages for ontology curation, LLM-based literature search, knowledge graphs (Neo4j), and automated annotation pipelines. If you are excited about the intersection of AI and scientific knowledge, this is a team where you will thrive. The Cellular Genomics programme at the Wellcome Sanger Institute applies single-cell genomics technologies combined with advanced computational methods to comprehensively map human cells - unravelling the intricate fabric of the human body, one cell at a time. Our researchers use transcriptomics, spatial analysis, and AI to create detailed reference maps of human cell types across tissues and organs, decode genetic and epigenetic controls in development and disease, and investigate conditions including immune disorders, childhood cancers, and reproductive tissue diseases. The programme is a key contributor to the Human Cell Atlas - the international effort to create comprehensive maps of all human cell types - and is committed to democratising scientific data for global access and studying diverse human populations. Essential Skills: PhD (or equivalent experience) in biological sciences, bioinformatics, or a computational discipline Programming experience in Python Ability to critically read and synthesise scientific literature across biological domains Knowledge of cell biology Self-motivation and ability to work independently in a small team Attention to detail Ability to develop collaborative working relationships with external partners and consortia Experience with single-cell transcriptomics or related genomics/bioinformatics approaches Familiarity with ontologies, controlled vocabularies or knowledge representation Other Information: For further details, please see role profile. Due to the fixed term nature of the funding, we are ideally looking for you to be able to start as soon as possible. Salary per annum: (dependent upon skills and experience):£45,803-£54,416 Closing Date: 14th June 2026 Hybrid Working a

Additional Information

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 recruiting a Computational Biologist role for a fixed term until 30th June 2027. Single-cell and spatial transcriptomics atlases combined with machine learning, are revolutionising our understanding of cell types and their function in health and disease than traditional methods can keep up. The Cell Ontology (CL) is the community standard that makes this knowledge computable, used by the Human Cell Atlas, the BRAIN Initiative, CellxGene, and thousands of researchers worldwide. We are looking for someone to help us extend it to cover the whole human brain and incorporate Human cell Atlas Organ atlases. This is not a conventional curation role. You will be pioneering agentic AI workflows that combine large language models, automated literature deep search, bioinformatic analysis, and knowledge graphs to curate cell type knowledge at a scale and speed that was not possible even a year ago. You will be working at the frontier of how AI transforms scientific knowledge engineering. You will be responsible for: Extending the Cell Ontology : add new cell types from Human Cell Atlas and BRAIN Initiative reference atlases, integrating evidence from literature, transcriptomics, and expert knowledge. Collaboratively building and running agentic AI workflows: develop Python-based workflows where AI agents search literature, extract evidence, run bioinformatic tests, and draft ontology entries for expert review. Collaborate internationally : work directly with scientists at the Allen Institute, CZI, and HCA partner institutions to annotate reference taxonomies and improve cell type standards. Contribute to open-source tools : help develop and maintain the team's growing suite of Python packages and Agentic Ai workflows for ontology curation, cell type mapping, and knowledge graph construction. About you: We welcome applications from two profiles - and everything in between: Biologists who code : you have deep knowledge of biology (any organ system or model organism) and are excited to learn AI-assisted workflows. You can read a paper critically and you're comfortable with Python. Computational scientists with a good grounding in biology: you have strong programming skills and experience with data pipelines, NLP, or knowledge engineering as well as a good grounding in biology.

Computational Biologist - Cell Ontology & Agentic AI Workflows

About the role

Benefits

Additional Information

Your Match

Company Intel

What employees say

Interested in this role?