Postdoctoral Researcher in Quantum Machine Learning for Drug Development

AstraZeneca is a global, science-led biopharmaceutical company. Within Pharmaceutical Sciences, we develop the therapies of the future by connecting deep scientific expertise with modern modelling and data science—helping teams move faster and make better decisions “from molecule to medicine”.

The Predictive Science Digital and Automation (PSDA) department works at the interface of experimental science, physical modelling, and AI/machine learning to accelerate development across e.g., synthetic routes, solid-state/formulation understanding, and developmentability, always with a focus on real-world impact for patients.

We are recruiting a Postdoctoral Researcher to lead a research project on how quantum machine learning (QML), with a focus on quantum kernel methods and learning in feature Hilbert spaces, could improve prediction of chemical properties relevant to drug development

The project will investigate whether performance and data efficiency can be improved by using higher-accuracy quantum representations beyond standard DFT and by applying QML methods.

The position is embedded within the Wallenberg Center for Quantum Technologies (WACQT), which provides a rich scientific ecosystem with world‑class experts in both theoretical and experimental quantum technology, offering a uniquely stimulating environment for advancing frontier research. You will join AstraZeneca’s Predictive Science Digital and Automation department and work closely with your academic supervisor, benefiting from access to leading quantum‑computing expertise and hardware.