Senior AI Scientist – Drug Discovery (Hybrid)

AstraZeneca plc; Cambridge; Hybrid; GBP 90,000 - 135,000; Full time

Job summary

AstraZeneca plc in the Cambridge area is seeking an expert in AI for Discovery–New Target Discovery. You will apply agentic AI and predictive biology tools to surface novel drug targets across Oncology and BioPharmaceuticals, working with cross‑functional teams to translate insights into actionable biology.

The role blends hands‑on AI development with target strategy, requiring strong Python, DL framework experience, and the ability to communicate complex results to diverse audiences.

Qualifications

• PhD or equivalent research experience in quantitative biology or AI.
• Experience with agentic AI,LLM‑based reasoning systems, or multi‑agent architectures.
• Experience with predictive AI modeling for biology including foundation models or graph neural networks.
• Understanding of drug discovery biology: target identification/validation.

Responsibilities

• Collaborate with scientists to identify challenges and apply AI to accelerate target discovery.
• Build and deploy multi‑agent AI systems within therapeutic workflows.
• Develop and benchmark predictive models for in silico biology and preclinical forecasting.
• Write production‑level code, pipelines and tools for the team and wider AZ organization.
• Communicate technical findings effectively to diverse audiences.
• Contribute to AstraZeneca’s external visibility through publications and collaborations.

Skills

Agentic AI

LLM reasoning

Multi-agent systems

Predictive AI modeling

Biology knowledge

Python

Scientific communication

Education

PhD in computational biology / bioinformatics / AI

Bachelor’s/Master’s with relevant research

Tools

PyTorch

JAX

Production‑quality pipelines

Job description

AstraZeneca plc in the Cambridge area is seeking an expert in AI for Discovery–New Target Discovery. You will apply agentic AI and predictive biology tools to surface novel drug targets across Oncology and BioPharmaceuticals, working with cross‑functional teams to translate insights into actionable biology.

The role blends hands‑on AI development with target strategy, requiring strong Python, DL framework experience, and the ability to communicate complex results to diverse audiences.