AI Security Institute (AISI)
Research Scientist (Biological Models), Chem-Bio
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About The AI Security Institute
The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We’re in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally.
We’re here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action.
The deadline for applying to this role is 6th September 2026, end of day, anywhere on Earth.
About The Team
AISI's Chem Bio (CB) team conducts technical research to assess evolving AI capabilities related to science R&D and CB misuse, and the effectiveness of technical safeguards that might mitigate risks arising from those capabilities.
The goal of our research is to inform critical decisions on security, opportunities, policy, and risk mitigation made by governments and AI developers.
We're a close-knit, unusually interdisciplinary team—made up of machine learning researchers and engineers, software engineers, virologists and bacteriologists, behavioural research scientists, biosecurity experts, long-standing CB policy specialists and talented generalists—who work closely with other technical and policy teams across government.
Over the next twelve months, CB will hugely scale the range and complexity of the evaluations and research programmes it carries out, and engage more deeply with partners in major AI labs, the wider biotech and pharma ecosystem and security services than it ever has before.
About The Role
AI capabilities in the life sciences are advancing faster than at any point in history. Foundation models can now design novel proteins and interpret genomic sequences. Specialised biological models can both identify drug targets and design the compound to target them. These are extraordinary tools for scientific progress but also have the potential for harm if misused.
This role is for a technical researcher who can contribute strong ML and computational biology expertise to that mission. You will sit within a group of research scientists, subject matter experts and engineers, leading empirical research into the risk-relevant capabilities of specialised biological models, including biomolecular structure and generative-design systems. You will translate ambiguous questions about what these models could enable into rigorous research questions and experimental designs, assess whether in-silico performance translates into meaningful experimental outcomes, and investigate whether technical safeguards can reliably limit potentially dangerous capabilities. It is a role at the interface of machine learning, computational biology and biosecurity: shaping which capabilities we investigate, how we measure their real-world significance, and how we translate our findings into decisions by government and other trusted partners.
What you will own
- Evaluate the risk-relevant capabilities of specialised biological models: Translate important but ambiguous questions about the capabilities of state-of-the-art biological models (including biomolecular structure and generative design models) into measurable research questions and experimental designs.
- Connect computational and experimental evidence: Use published experimental results, biological datasets, expert review and, where appropriate, external wet-lab collaborations to assess whether in-silico performance translates into experimentally relevant outcomes.
- Identify feasibility and effectiveness of technical safeguards: Lead research into the feasibility and effectiveness of technical safeguards for specialised biological models, including access controls, model-level interventions, monitoring, detection and capability-limiting approaches.
- Track the technical frontier: Identify important developments in biological AI and determine which new models, methods or capabilities AISI should investigate. Help shape the team’s research agenda as the field evolves.
- Communicate to decision-makers: Produce clear technical reports, briefings and recommendations for senior decision-makers within government and other trusted partners, translating a complex technical evidence base into actionable conclusions that inform wider cross-Government and industry efforts in this space.
- Collaborate across expert communities: Work closely with research scientists, engineers, biosecurity experts, policy teams, AI safety specialists and external scientific partners to ensure AISI’s evaluations are technically rigorous and policy-relevant.
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Role requirements
- Deep, hands-on experience working with biological machine learning models. You have worked directly with biological AI models, such as protein design models, generative, structure prediction or scientific foundation models.
- Strong machine-learning background and applied engineering skills. You understand modern machine-learning methods and have practical experience training, fine-tuning, adapting or evaluating models using PyTorch or similar. You can write robust, readable and maintainable Python code.
- Computational biology expertise. You have sufficient understanding of molecular biology, biochemistry, structural biology, protein science, genomics or a related area to reason seriously about biological data, model outputs and the scientific validity of an evaluation.
- Strong empirical judgement. You know how to design experiments to answer pre-specified research questions, identify relevant baselines/controls for these experiments and critically interpret scientific results. You can identify limitations in public benchmarks, evidential gaps and cases where results are being over- or under-interpreted.
- Mission orientation. You are motivated to conduct technical research with direct public-interest and policy impact. You understand that work at the intersection of AI and biology may carry dual-use sensitivity and can operate with appropriate discretion.
- Collaborative interdisciplinary communication. You can explain complex findings and their uncertainty across audiences, from researchers, engineers, subject-matter experts, policy and security stakeholders, without blurring the bottom line, and work effectively with people from very different technical backgrounds.
Strong Candidates May Also Have
- AI safety framework familiarity. Understanding of AI safety frameworks, model evaluations, responsible capability assessment, release governance or other approaches to managing risks from advanced AI systems.
- Relevant institutional experience. Experience working in or with organisations such as Dstl, MOD, DHSC, UKHSA, academia, public health bodies, frontier AI labs, biotech companies, national security organisations or equivalent institutions in other settings.
- Existing security clearance. Existing SC or DV clearance
- AI-enabled research experience. Experience using AI tools to accelerate research, analyse biological data, support literature review, develop benchmarks or improve scientific workflows.
- Deep domain expertise in a relevant area of the life sciences. Specialist knowledge in one or more fields such as protein design, structural biology, virology, immunology, genomics or epidemiology, giving you an additional lens through which to assess the significance of model capabilities and outputs.
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Other Core Requirements
- You should be able to spend at least 9 days per fortnight working with us.
- You should be willing to work from our office in London at least 3 days/week.
- You should be UK-based.
Security Clearance
Appointment is conditional on successfully completing UK Government SC clearance. Prior clearance is not required—we will sponsor and support you. You should normally have been resident in the UK for the past 5 years.
You will also be required to undergo Developed Vetting (DV). DV typically requires a longer period of UK residency (around 10 years). Employment is conditional on obtaining and maintaining the required clearance(s). More detail on clearance eligibility can be found on the UK Government website: National security vetting: clearance levels - GOV.UK.
Selection process
- Application - CV and short application questions.
- Screening interview - Lightweight conversation on relevant skills, motivation and fit.
- Technical take home test - A take-home exercise designed to test your applied subject matter expertise and judgement in context. You will receive this after the screening interview.
- Technical interview - Discussion of your work test with a current AISI SME.
- Behavioural interview - Deeper dive on non-technical skills needed to succeed in the role: communication skills, judgement and team dynamics.
- Senior leadership interview (30 min) - Final conversation with AISI senior leadership.
What We Offer
Impact you couldn't have anywhere else
- Incredibly talented, mission-driven and supportive colleagues.
- Direct influence on how frontier AI is governed and deployed globally.
- Work with the Prime Minister’s AI Advisor and leading AI companies.
- Opportunity to shape the first & best-resourced public-interest research team focused on AI security.
Resources & access
- Pre-release access to multiple frontier models and ample compute.
- Extensive operational support so you can focus on research and ship quickly.
- Work with experts across national security, policy, AI research and adjacent sciences.
Growth & autonomy
- If you’re talented and driven, you’ll own important problems early.
- 5 days off and annual stipends for learning and development, and funding for conferences and external collaborations.
- Freedom to pursue research bets without product pressure.
- Opportunities to publish and collaborate externally.
Life & family*
- Modern central London office, or where applicable, option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol.
- Hybrid working, flexibility for occasional remote work abroad and stipends for work-from-home equipment.
- At least 25 days’ annual leave, 8 public holidays, extra team-wide breaks and 3 days off for volunteering.
- Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option for additional unpaid time).
- On top of your salary, we contribute 28
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