AI Computational Chemist - Senior Scientist

ASTRAZENECA UK LIMITED; Hartford; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading biopharmaceutical company in the UK is seeking an AI-specialist Computational Chemist to drive AI-driven molecular design for oncology projects. You will apply advanced machine learning and cheminformatics methods to enhance drug discovery and decision-making. The successful candidate will have a PhD in Chemistry or related fields and strong expertise in AI and computational techniques. This role fosters a collaborative environment where innovative ideas are valued, and you will have opportunities to publish your findings.

Qualifications

• Strong knowledge of machine learning and computational chemistry.
• Experience in predictive or generative AI/ML methods in chemistry.
• Proficiency in programming and pipelining tools.

Responsibilities

• Lead AI-driven molecular design strategies using generative AI.
• Build and validate machine learning models for various properties.
• Convert computational insights into clear design hypotheses.
• Create cheminformatics pipelines and automated decision-support tools.
• Evaluate and drive adoption of new AI methodologies across teams.
• Present complex results to multidisciplinary audiences.

Skills

Machine learning

Computational chemistry

Cheminformatics

Python programming

RDKit

Data analysis

Education

PhD in Chemistry or related discipline

Tools

scikit-learn

PyTorch

DeepChem

Job description

Overview

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.

Responsibilities

• Own AI-driven molecular design strategies: Lead the application of generative and predictive AI—including our in-house REINVENT platform—to propose, optimize, and prioritize 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 rigour 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.

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

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. 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.