PhD position in Physics-Inspired AI for Drug Design University of Basel in Switzerland

The University of Basel is offering a fully funded PhD position in the Computational Pharmacy group, focusing on the development of physics-inspired artificial intelligence (AI) methods for drug design. This research aims to advance next-generation drug discovery by integrating physicochemical principles directly into deep neural network models, addressing the limitations of purely data-driven approaches in modeling protein–ligand interactions. The group has a strong publication record in this area, with recent work demonstrating the need for more generalizable AI models in life sciences.

The successful candidate will contribute to ongoing projects that combine physics-based modeling with state-of-the-art machine learning techniques. The main objective is to create a next-generation docking framework that explicitly incorporates protein–ligand dynamics, enabling more accurate predictions and real-world validation through collaboration with experimental research groups. Responsibilities include designing and implementing innovative deep neural network architectures, integrating physical principles and molecular modeling knowledge, and working closely with interdisciplinary teams.

Applicants should have a Master’s degree in Physics, Computational Chemistry, or Computer Sciences, with excellent knowledge in statistical mechanics and thermodynamics. Research experience, preferably with publication, is expected, along with strong programming skills in Python and familiarity with machine learning, especially neural network concepts. Fluency in English and a collaborative, motivated attitude are essential.

The position offers training in key methods of an emerging research field, access to an international and collaborative research environment, and the opportunity to work at the forefront of computational drug design. The PhD is fully funded, covering tuition and stipend. The position is available immediately, and applications should be submitted via the online recruiting platform. Required documents include a motivation letter, CV, diplomas, and contact details for at least two academic references. For further information, candidates can visit the Computational Pharmacy group’s website or contact Prof. Markus Lill directly.

Application deadline: 5 June 2026. For more details and to apply, visit the official application link.