AI Computational Chemist - Senior Scientist

AstraZeneca; Cambridge; On-site; GBP 80,000 - 100,000; Full time

Job summary

A leading global biopharmaceutical company seeks an AI Computational Chemist - Senior Scientist in Cambridge, UK. You will lead AI-driven molecular design for oncology, collaborating with multidisciplinary teams. A PhD in Chemistry and strong machine learning skills are essential. The role offers competitive benefits and opportunities for publication and presentation at conferences. Join us to shape the future of drug discovery at a forefront company.

Benefits

Competitive salary

Excellent employee benefits

Opportunities for publication and presentation

Qualifications

• PhD (or equivalent experience) in Chemistry, Computational Chemistry, or closely related discipline.
• Strong knowledge of machine learning methods and algorithms.
• Demonstrated experience with predictive or generative AI in chemistry.

Responsibilities

• Lead AI-driven molecular design strategies and research.
• Develop and deploy predictive models for drug discovery.
• Communicate complex results to multidisciplinary teams.

Skills

Machine learning

Computational chemistry

Cheminformatics

Programming (Python)

Data analysis

Education

PhD in Chemistry or related field

Tools

RDKit

scikit-learn

PyTorch

Job description

Job Title: AI Computational Chemist - Senior Scientist

Location: Cambridge, UK

Salary: Competitive + Excellent Employee Benefits!

Introduction to the Role

Join AstraZeneca’s Oncology R&D in Cambridge, UK as an AI‑specialist Computational Chemist and help shape the future of drug discovery. AstraZeneca is at the forefront of applying AI‑powered drug design—including generative molecular design, predictive modelling, and advanced cheminformatics—to accelerate the creation of novel medicines.

About the Role

In this role, you will lead AI‑driven design across multiple oncology projects, applying structure‑ and ligand‑based methods, machine learning, and generative AI to craft molecules with the right balance of potency, selectivity, and developability. You will operate in a highly collaborative environment with medicinal chemists, biologists, data scientists, and DMPK experts, and you’ll be encouraged to publish and present your work at leading conferences.

Expectations of a Successful Candidate

• Own AI‑driven molecular design strategies: Lead the application of generative and predictive AI — including our in‑house REINVENT platform — to propose, optimise, and prioritise compounds for complex oncology targets, translating hypotheses into project decisions.
• Develop and deploy predictive models: Build and validate machine learning models for bioactivity, selectivity, ADME/DMPK, and physicochemical properties, integrating them into routine project workflows.
• Deliver tangible project impact: Convert computational insights into clear design hypotheses, higher‑quality compounds, and faster progression toward candidate selection and development milestones.
• Build scalable workflows: Create and maintain cheminformatics pipelines and automated decision‑support tools that enhance speed, reproducibility, and rigor across teams.
• Champion innovation and best practice: Evaluate emerging computational methodologies and AI technologies; drive adoption across global teams in Cambridge, Boston, and Gothenburg.
• Communicate and influence: Present complex results clearly to multidisciplinary audiences, guide experimental plans, and contribute to project strategy and portfolio decisions.
• Publish externally: In high‑quality journals and present at national and international conferences.

Required Skills and Qualifications

• Education: PhD (or equivalent experience) in Chemistry, Computational Chemistry/Cheminformatics, or a closely related discipline.
• Core expertise: Strong knowledge of machine learning, computational chemistry, and cheminformatics. Knowledge of a range of machine/deep learning algorithms and architectures (e.g. graph neural networks, transformers).
• AI application: Demonstrated interest and significant practical experience building and applying predictive or generative AI/ML methods in a chemistry context.
• Programming and workflows: Proficiency with RDKit and Python (and/or R, C++, Java), libraries for ML (e.g. scikit‑learn, PyTorch, DeepChem), and experience with pipelining tools.
• Computational chemistry methods breadth: Knowledge and understanding of protein structure and dynamics modelling, and structure / ligand‑based design.
• Medicinal chemistry fundamentals: Good knowledge of physicochemical and ADME properties and their impact on molecule quality and progression.
• Ways of working: Excellent communication, presentation, teamwork, influencing, and time‑management skills.

Desirable Skills and Qualifications

• Generative and predictive AI in drug discovery: Experience of applying these methods on live projects to design new drugs and model their properties.
• Drug discovery impact: Proven experience applying structure‑ and ligand‑based methods in live projects, delivering measurable outcomes.
• Publications: Peer‑reviewed publications in computational chemistry, cheminformatics, or AI for drug discovery.

About AstraZeneca

AstraZeneca is a global, science‑led biopharmaceutical company committed to transforming patients’ lives through innovative medicines. In Oncology R&D, we combine deep biological insight with state‑of‑the‑art AI to accelerate molecular design and decision‑making. Our teams operate in an open, collaborative environment across Cambridge (UK) and Boston (USA), sharing best practice and pushing the boundaries of computational chemistry and machine learning. By joining us as a Senior Scientist, you will contribute to a vibrant community of scientists pioneering AI‑enabled drug design—and have the platform to publish, present, and shape the next wave of innovation.

Ready to make a significant impact?

Apply now and join us on this exciting journey!

So, what’s next?

Are you ready to bring new insights and fresh thinking to the table? Brilliant! We have one seat available, and we hope it’s yours. We encourage you to apply online before midnight on January 25th.

Where can I find out more?

Social Media:

Follow AstraZeneca on LinkedIn
https://www.linkedin.com/company/1603/
Follow AstraZeneca on Facebook
https://www.facebook.com/astrazenecacareers/
Follow AstraZeneca on Instagram
https://www.facebook.com/astrazenecacareers/

Date Posted

05-Jan-2026

Closing Date

25-Jan-2026

We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.