Doctoral researcher (PhD student) in Quantum Machine Learning Force Fields for Molecule-Protein Interactions

Updated: over 1 year ago
Deadline: ;

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The University was founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University’s faculties and interdisciplinary centres focus on research in the areas of Computer Science and ICT Security, Materials Science, European and International Law, Finance and Financial Innovation, Education, Contemporary and Digital History. In addition, the University focuses on cross-disciplinary research in the areas of Data Modelling and Simulation as well as Health and System Biomedicine. Times Higher Education ranks the University of Luxembourg #3 worldwide for its “international outlook,” #20 in the Young University Ranking 2021 and among the top 250 universities worldwide.

The University of Luxembourg invites applications to the following vacancy in the Department of Physics and Materials Science (http://dphyms.uni.lu/ ) within its Faculty of Science, Technology and Medicine: Doctoral researcher (PhD student) in Quantum Machine Learning Force Fields for Molecule-Protein Interactions

The University of Luxembourg is looking for a doctoral candidate to start working on the project “Quantum Machine Learning Force Fields for Molecule-Protein Interactions” funded by the H2020-MSCA-ITN-2020 (http://ai-dd.eu/ ). Computational modelling of drug-protein binding is of vital importance in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel candidates for biological targets, genetic studies, and gene technology. The recent combination of machine learning (ML) to accelerate quantum-mechanical (QM) calculations has already led to breakthroughs in our ability to obtain dynamical insights into small molecules. However, large realistic molecules remain out of reach of QM/ML approaches. Hence, this project aims at the development and validation of reliable QM/ML force fields to investigate the dynamics of drug-protein systems of pharmaceutical relevance.

The candidate will be integrated into the activities of the Theoretical Chemical Physics group lead by Prof. Alexandre Tkatchenko (www.tcpunilu.com ) for the first half of the doctoral studies (18 months) while the second half will be carried out at AstraZeneca under the supervision of Dr. Ola Engkvist (Sweden, 18 months). This project will allow the candidate to interact with the scientific staff from some of the world’s top universities and pharmaceutical companies.



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