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- Tasks: Lead AI-driven molecular design and collaborate on innovative oncology projects.
- Company: Join AstraZeneca, a global leader in biopharmaceuticals, transforming lives through innovative medicines.
- Benefits: Competitive salary, excellent employee benefits, and opportunities for professional growth.
- Why this job: Make a real impact in drug discovery using cutting-edge AI technologies.
- Qualifications: PhD in Chemistry or related field with strong machine learning expertise.
- Other info: Collaborative environment with opportunities to publish and present at conferences.
The predicted salary is between 43200 - 72000 ÂŁ per year.
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.
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.
AI Computational Chemist - Senior Scientist in Cambridge employer: AstraZeneca
Contact Detail:
AstraZeneca Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Computational Chemist - Senior Scientist in Cambridge
✨Tip Number 1
Network like a pro! Reach out to current employees at AstraZeneca on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Make sure you can confidently discuss machine learning algorithms and computational chemistry methods. Practise explaining complex concepts in simple terms, as you'll need to communicate with multidisciplinary teams.
✨Tip Number 3
Showcase your passion for AI in drug discovery! Be ready to discuss any projects you've worked on that involved generative or predictive AI. Highlight how your work has made an impact, and don’t forget to mention any publications or presentations you've done.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're serious about joining AstraZeneca. Don’t forget to tailor your application to highlight your relevant experience in AI and computational chemistry.
We think you need these skills to ace AI Computational Chemist - Senior Scientist in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your expertise in AI, computational chemistry, and any relevant projects you've worked on. We want to see how you can contribute to our innovative team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI in drug discovery and how your background makes you a perfect fit for the role. Let us know what excites you about working with AstraZeneca!
Showcase Your Projects: If you've worked on any relevant projects, especially those involving machine learning or cheminformatics, make sure to mention them. We love seeing practical applications of your skills, so don’t hold back on the details!
Apply Through Our Website: We encourage you to apply directly through our website for a smooth application process. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at AstraZeneca
✨Know Your AI and Chemistry Inside Out
Make sure you brush up on your knowledge of machine learning algorithms and computational chemistry methods. Be ready to discuss how you've applied these in real projects, especially in drug discovery. This will show that you not only understand the theory but can also implement it effectively.
✨Prepare for Collaborative Scenarios
Since this role involves working closely with medicinal chemists, biologists, and data scientists, think about examples from your past where you successfully collaborated across disciplines. Be prepared to share how you communicated complex ideas clearly to non-experts, as this is crucial in a multidisciplinary environment.
✨Showcase Your Problem-Solving Skills
Think of specific challenges you've faced in previous roles related to molecular design or predictive modelling. Prepare to discuss how you approached these problems, the solutions you implemented, and the outcomes. This will demonstrate your ability to deliver tangible project impact.
✨Engage with Their Vision
Familiarise yourself with AstraZeneca's current projects and their approach to AI in drug discovery. During the interview, express your enthusiasm for their work and how your skills align with their goals. This shows that you're not just looking for any job, but are genuinely interested in contributing to their mission.
