PostDoc position in AI-based Drug Discovery – Basel, Switzerland

The Division of Computational Pharmacy, Department of Pharmaceutical Sciences, is offering a PostDoc position to develop and apply cutting-edge computational methodology integrating physicochemical knowledge into deep neural network algorithms for drug discovery applications. The project will focus on the efficient and accurate sampling of protein-ligand conformational states, i.e. protein-ligand co-folding.
Your assignments

The PostDoc position is available to extend ongoing research on the development of novel algorithms for drug design combining physics-based modeling with deep neural network concepts. You will be responsible for the development and implementation of novel deep neural network models based on recent developments in diffusion models and GFlowNets.

• PhD in the fields of Physics, Physical/Computational Chemistry, Mathematics or Computer Sciences
• Strong programming skills
• Strong experience in developing and applying deep neural network concepts
• Knowledge in generative models, e.g. diffusion models, is desirable
• Fluent verbal and written communication skills in English
• Highly motivated, interactive team player

• PostDoc position
• Opportunity to work with and develop emerging technologies in the field of Computational Drug Design
• International and collaborative research environment
• Possibility to increase your academic profile and supervise junior researchers

Application / Contact

Please submit your complete application documents, including

• Letter (max. 1 page) highlighting motivation, scientific experience and skills
• CV
• Publication list
• Short summary (including citation) to 2-3 most relevant publications
• Diploma of PhD degree (if PhD degree completed)
• Contact details of at least two academic references

via the online recruiting platform.

Position is available starting 1. December 2023. You can find out more about us at https://pharma.unibas.ch/de/research/research-groups/computational-pharmacy-2155/

For questions, please contact Dr. Amr Abdallah (amr.abdallah@unibas.ch) or Prof. Markus Lill (markus.lill@unibas.ch).