Proteins play a crucial role as mediators of the therapeutic potential of molecules. Capturing meaningful information on proteins with AI has an enormous potential in drug discovery and chemical biology, e.g., for structure-based drug discovery and polypharmacology. Despite such potential, strategies to capture sophisticated information on protein structure with AI are underexplored compared to small molecules.
This ERC-funded project has the ambitious goal to develop new AI strategies to learn efficiently from protein structures, to accelerate small molecule drug discovery. The project will be fueled by methodological innovation and aimed to leverage large corpora of protein data with cutting-edge deep learning algorithms. The developed approaches will be applied experimentally for structure-based drug discovery, thereby providing a unique opportunity to validate the AI predictions in a real-world setting.
Your tasks will include:
You will work at the interface between AI, chemistry, and biology, with a proactive and interdisciplinary attitude. You will become a member of the Molecular Machine Learning team (led by Dr. F. Grisoni), whose mission is to augment human intelligence in drug discovery with novel AI technology. You will also be embedded in the Chemical Biology group, the Dept. of Biomedical Engineering, the Institute for Complex Molecular Systems, and the Eindhoven AI Systems Institute, which are characterized by a highly interdisciplinary and collaborative approach to science and research.
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
Do you recognize yourself in this profile and would you like to know more?
Please contact dr. Francesca Grisoni, f.grisoni[at]tue.nl.
Visit our website for more information about the application process or the conditions of employment. You can also contact Sascha Sanchez, HR advisor, s.j.m.g.sanchez.van.oort[at]tue.nl or +31 40 247 73 10.
Are you inspired and would like to know more about working at TU/e? Please visit our career page.
We invite you to submit a complete application using the apply-button. The application should include a:
We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.