Are you a cheminformatic data scientist with a passion for applying AI methods to drug discovery? Do you want to contribute to the discovery of new therapies for cancer treatment? If so, we have an exciting opportunity for you. Join our high-performing team working on a diverse range of pre-clinical projects in the Oncology Chemistry Department. Your work will have a direct impact on the development of new drugs to treat cancer.

Accountabilities:
As a Senior AI Scientist, you will be responsible for impacting multiple discovery projects simultaneously by efficiently applying a wide variety of machine learning, cheminformatics workflows & artificial intelligence methods. You will build machine learning models for target activity prediction and ADMET endpoints, produce cheminformatics workflows to accelerate computational drug design, and implement generative AI models for molecular de novo design on projects. You will also drive scientific progress in applying machine learning in drug discovery through cross-functional collaboration and publish and present your work both internally and externally.

Essential Skills/Experience:
- A PhD (or equivalent experience) in Chemistry, Computational Chemistry/Cheminformatics or a related discipline.
- A broad knowledge of computational chemistry, cheminformatics and machine learning concepts.
- Knowledge of a variety of machine/deep learning algorithms/architectures (e.g. Transformers, RNNs, GNNs, CNNs, GANs, Diffusion, SVM, Random Forest, Linear Regression).
- Expertise in programming (Python preferred) and pipelining tools.
- Expertise in building predictive machine learning models relevant for drug discovery.
- An appreciation of physicochemical properties and DMPK and their importance in medicinal chemistry.
- Appreciation of generative de novo design tools, including scoring functions.
- Excellent communication, presentation, team working and influencing skills.
- Excellent time management, forward planning and delivery focus.

Desirable Skills/Experience:
- Experience in applying generative and predictive AI methods to medicinal chemistry problems in a drug discovery setting, delivering tangible outcomes.
- Publications in computational chemistry or AI/Machine Learning fields.
- Experience with ligand and structure-based drug design and with appropriate tools, including virtual screening, ligand docking and methods to estimate binding free energy (e.g. FEP).
- Experience in running and analysing molecular simulations (e.g. molecular dynamics).

Location: Cambridge, UK

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions.

That’s why we work, on average, a minimum of three days per week from the office. But that doesn't mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

At AstraZeneca, we follow the science and pioneer new frontiers. We are dedicated to Oncology, with an ambition to eliminate cancer as a cause of death. Our big vision unites and inspires us. With multiple indications and high-quality molecules at all stages of our innovative pipeline, we keep pushing forward. Fusing ground breaking science with the latest technology to achieve breakthroughs. Backed by investment, we are aiming to deliver 6 new molecular entities by 2025.

Are you ready to make a difference? Apply today!

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