Bioinformatics Scientist

Bioinformatics Scientist LocationLondonEmployment TypeFull timeLocation TypeOn-siteDepartmentDataAbout UsBasecamp Research is dedicated to solving major challenges in the life sciences by exploring Beyond Known Biology. Our teams build frontier AI models using BaseData, the world's largest ethically-sourced and globally representative biological dataset. Our Global Research Team collects and curates our own biological data through partnerships with more than 152 organisations in 28 countries, giving its AI access to genetic diversity that doesn't exist for models trained on public database sources. This enables Basecamp Research to design novel protein sequences and biological systems that can accelerate therapeutic research and development.In October 2024 we closed Series B and in January 2026 finalised pre-Series C investment from NVIDIA. With hubs both in London, UK as well as Boston, Massachusetts, USA and partners with biopharma companies and academic institutions worldwide, our work has been recognised with honours including Fast Company's Top 10 Most Innovative Companies in Biotech and the FT-backed Sifted AI100 list of Europe's leading AI startups.At Basecamp Research, we pride ourselves on being a diverse, exciting, fun, and flexible place to work. Our team of biologists, engineers, ML scientists, field explorers, and operations specialists are united by a sense of adventure and the belief that nature has already designed the solutions to our planet's greatest challenges - we just need to go out and discover them! If you feel passionate about the power of biology, data, and AI to build a better world, we'd love to hear from you.The RoleWe are looking for a Bioinformatics Scientist to join our Genomics team in London. You will turn vast, heterogeneous, often downright strange biological data into annotated, trustworthy resources the rest of the company and our models can build on.We are building biological datasets at a scale no reference database has approached. Our flagship effort, the Trillion Gene Atlas, is one of the largest long-read sequencing efforts to date, targeting a trillion genes and a quadrillion assembled nucleotides.The heart of this role is understanding the data itself. Much of what we collect doesn't fit existing schemas or tools, so the job is not to just run a standard toolchain but to develop new methods that label and mine biology no one has characterised before. Because you understand both the biology and what the models need downstream, you know what the data has to become, not just correct but machine-readable and model-ready.What you'll doAnalyse diverse, messy biological datatypes, primarily microbiomes from a wide range of sample types, spanning both prokaryotes and eukaryotes, bringing the biological judgment to know when an annotation is a real signal versus an artefact.Develop new methods and tools to label and mine this data.Design approaches for biology that doesn't fit standard schemas, curate the data to be model-ready, and benchmark honestly to tell real improvement from noise.Prototype methods and validate on real, messy data at scale. Own light orchestration to prove or disprove an approach, then hand off to dedicated teams who take it to full production scale.Reach for newer ML methods where they are the right tool for annotation, labelling, or mining, and fold them into your approach cleanly.Keep the data trustworthy. Provenance, edge cases, and data integrity are part of the craft, not an afterthought.Help build outward-facing tools where the opportunity arises. For example, a predictive "oracle" that helps our field teams target regions of the planet where undiscovered biodiversity is most likely to be found, turning curated data back into smarter sampling and discovery.About YouYou have a deep understanding of biological data and a strong core in sequence informatics (alignment, annotation, sequence analysis), with the judgment to know when standard tools are misleading or...