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Forward Deployed Scientist

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Adaptyv
Full Time position
Listed on 2026-10-14
Job specializations:
  • Research/Development
    Biotech Research, Research Scientist, AI Business & Operations
Salary/Wage Range or Industry Benchmark: 70000 - 110000 GBP Yearly GBP 70000.00 110000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Adaptyv is building an automated lab that lets AI agents run biology experiments.

We’re entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can’t run the experiments themselves - that’s still a manual, months-long process. We’re building the infrastructure that gives AI agents access to the physical world.

We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today.

Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development.

We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation.

About the Role

You work with customers to help them design better proteins and get more out of every experiment, sitting between their design models and our lab.

In London, a large share of that work is with ARIA. Adaptyv has been selected for ARIA’s second cohort of Activation Partners, and ARIA, the UK’s Advanced Research + Invention Agency, is funding our new automated lab in London: the UK’s first AI-native automated wet lab.

ARIA backs ambitious research programmes across areas such as engineering human immunity, protein-based materials and synthetic plants. The teams it funds, called Creators, often need experimental capabilities that do not yet exist. You’ll work directly with those teams to define what needs to be built, develop the assays, and bring them onto our automation platform.

Our goal is to help the next 100 UK biotechs and neopharmas get started by the end of 2028.

What You’ll Do
  • Lead scientific projects with customers. Translate biological questions into clear protein design and experimental strategies, including targets, success criteria, constructs, controls and assays.

  • Guide protein design strategy. Help teams choose the right approaches for the problem, from de novo and diffusion-based design to protein language models, structure prediction and physics-based methods.

  • Turn data into decisions. Analyse binding, expression, stability and other assay data with customers and determine what the next round of designs should test.

  • Develop new experimental capabilities. When an ARIA programme needs an assay that does not yet exist, work with the Creator team and our scientists to develop it, validate it and bring it onto the automation platform.

  • Shape future ARIA programmes. Work with ARIA Programme Directors to understand the experimental capabilities upcoming Creator cohorts are likely to need and help us prepare for them.

  • Build long-term scientific partnerships. Become a trusted scientific counterpart to the teams you work with, and bring what you learn back into our product, science and platform roadmap.

What We’re Looking For
  • Strong protein science foundation. A degree and/or hands-on experience in protein design, computational biology, biochemistry, structural biology or a related field.

  • Biophysical characterisation experience. Deep hands-on experience with SPR, BLI, nanoDSF or related methods is required.

  • Fluency in modern protein design. You understand the major approaches used in the field, their strengths and limitations, and how to apply them to real design problems.

  • Strong quantitative instincts. …

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