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Senior Research Scientist, Mathematical Foundations

£24.8 - £28.9 per hourEstimated
Full-time

About Us

Basecamp 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 organizations 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 recognized with honors 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. 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 Role

We are looking for a Senior Research Scientist to join our AI Research team in London. You will work at the intersection of mathematics and machine learning, bringing rigorous quantitative thinking to some of the most challenging problems in biological AI.

Our research group is small, collaborative, and operates more like a frontier research lab than a typical biotech team. We train large-scale foundation models on the world's largest and richest metagenomic datasets, and we look for people who can push the mathematical boundaries of what these models can learn and represent. The work requires developing new methods and theories from scratch.

This is a role with real ownership. You will shape a research direction within the team, publish at top venues, and see your work translated into models that generate genuinely novel biology. The problems are hard, the data is unique, and the impact is tangible.

You'll be reporting to the Head of AI Research and working alongside researchers covering genomics, sequence modeling, and large-scale deep learning, as well as biologists, bioinformaticians, and engineers across the wider company.

About You

PhD in mathematics, physics, or a closely related quantitative field. Your work in AI and machine learning is driven by curiosity, and you've brought a depth of mathematical thinking that clearly distinguishes your work.

You have spent meaningful time on frontier research and you already have an understanding of how top research teams operate, from problem selection to large-scale experimentation to shipping results that matter.

Your research interests might span generative models, geometric deep learning, probabilistic modeling, dynamical systems, information geometry, optimization theory, or related areas. What matters most is that you think from first principles and bring mathematical structure to hard problems.

You have a strong publication record at top ML venues (NeurIPS, ICML, ICLR, or equivalent) that demonstrates independent thinking and a coherent research arc.

You are genuinely curious about biology. Domain expertise is welcome, and what we really care about is that you find it exciting to work with data from unexplored ecosystems encoding billions of years of evolutionary optimization. The best candidates will see biological data as a source of fundamentally new scientific questions.

You have low ego, strong collaborative instincts, and a startup mentality. You are comfortable with ambiguity, willing to iterate fast, and happy to work in a small team where everyone contributes across boundaries.

Nice to Have

Experience training models at large scale (billions of parameters, extreme long context, distributed training, custom architectures).

Domain knowledge in life sciences, genomics, or computational biology, e.g., familiarity with protein structure, molecular dynamics, or related biophysical methods.

What we offer in return

  • Impactful Mission: This is a rare chance to do work that genuinely matters. You'll join a talented, fast-moving team, access unique biological datasets at scale, and see your contributions shape real breakthroughs in AI and curative therapeutics..

  • Collaborative Culture: You'll be surrounded by world-class engineers, scientists, and researchers who care deeply about their work and about each other. With offices in London and Boston, we've built a flexible, cross-functional environment where personal development and real ownership aren't just talking points.

  • High Growth: We truly believe in investing our people we make coaching available to team members during steep growth journeys and we have twice yearly promotion opportunities. People who are really successful here own it and go directly to solve problems at pace and we ensure reward increases with impact.

  • Comprehensive Benefits: We've built a benefits package people value. That means competitive salary, equity, and private healthcare with no medical history exclusions so strong that means most employees' family members opt into our plan over their own. We also offer Carrot Fertility with IVF stipend, salary sacrifice pension, bike to work scheme, life insurance, and more.

We are committed to equal opportunity employment regardless of ethnic or national origin, race, religion, sex, age, citizenship, sexual orientation, marital status, disability, gender identity or any other basis. If you have a disability or additional need that needs accommodating do let us know.

Vacancy posted 11 hours ago
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