Senior AI Biologist & Scientific Staff Shape AI Discovery

Applied Geometry; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Competitive pay

Equity package

Private medical and dental cover

Budget for tooling and infrastructure

Conference funding

Team meals

Flexible time off

Job summary

Applied Geometry is an AI research lab building biological superintelligence. We train agents to reason from incomplete evidence, and discover biology and therapies. This hands‑on scientific role involves working with founders and engineers on challenging, high‑impact problems.

As an early team member you’ll define rigorous tasks, curate data, and implement reproducible analyses in Python or R while helping shape our scientific standards and culture.

Qualifications

• PhD in biology or closely related field with deep domain knowledge.
• Strong judgement and ability to evaluate evidence.
• Hands-on experience turning raw data into reproducible conclusions.
• Experience with Python or R for data analysis.

Responsibilities

• Design scientific tasks grounded in real research questions.
• Curate experimental datasets and identify uncertainties.
• Build reproducible analysis pipelines in Python or R.
• Develop defensible reference solutions and evaluation criteria.
• Stress-test agent reasoning and catch non-robust conclusions.
• Collaborate with research engineers to translate tasks into RL environments.
• Help define scientific standards and priorities.

Skills

Deep biology

Scientific judgement

Hands-on research

Quantitative skills

AI-agent fluency

High agency

Intellectual honesty

Education

PhD in biology

Computational biology

Bioinformatics

Tools

Python

R

Reinforcement Learning

Job description

Applied Geometry is an AI research lab building biological superintelligence. We train agents to reason from incomplete evidence, and discover biology and therapies. This hands‑on scientific role involves working with founders and engineers on challenging, high‑impact problems.

As an early team member you’ll define rigorous tasks, curate data, and implement reproducible analyses in Python or R while helping shape our scientific standards and culture.