A PhD position is available in the Theoretical Chemical Physics (TCP, http://www.tcpunilu.com) group, led by Prof. Alexandre Tkatchenko in the Physics and Materials Science Department (DPhyMS) at the University of Luxembourg (https://wwwen.uni.lu/research/fstm/dphyms)

The successful candidate will join a strong and highly-motivated research team with an excellent funding track-record in competitive national, international, and European grants, including an Advanced Grant by the European Research Council for a “Field-Theory Approach to Molecular Interactions”. The scientific topics of research range from machine learning approaches for describing molecular potential-energy surfaces, development of improved quantum methods for the description of non-covalent interactions, path-integral approaches to dynamics of molecular systems, and synergies between these methods to interpret puzzling experimental observations and predict new phenomena in complex molecular systems.

The University of Luxembourg is a young, dynamic, and well-funded university and is rapidly growing in international rankings. Luxembourg is a small European country with a very high quality of living and is bordered by France, Belgium, and Germany.

The position is open to strong applicants with backgrounds in physics, mathematics, computer science, and/or multidisciplinary background. UL and DPhyMS strive to increase the share of female PhD students. Therefore, we explicitly encourage women to apply. We offer a competitive salary and an attractive working environment in one of the most enjoyable European cities:  http://www.euraxess.lu

The PhD work will investigate the prediction of the structure and stability of different phases of molecular crystals, especially those with therapeutic potential. The prediction of the stable crystalline phases of therapeutic drugs is essential for the creation of safe and effective treatments and is an open question of great importance to the pharmaceutical industry. Over the years the TCP group has developed world-leading expertise in the prediction of stable phases of molecular crystals via advanced density functional methods. The PhD project will have two stages. First, the PhD student will learn and apply these methods in collaboration with industry on new pharmaceuticals to gain experience with ab initio methods and the material science of molecular crystals. Second, using this expertise, the student will pioneer new techniques to predict the stability of molecular crystals using cutting-edge machine learning methods in the hopes of developing a game-changing method of unparalleled accuracy and cost effectiveness. The Ph.D. student will need good mathematical and programming skills, a perfectionistic attention to detail, tenacity, a good understanding of basic quantum mechanics, physical and chemical intuition, and the desire to put their abilities to the test on a research topic that has the potential to improve people’s lives.

For more information and applications contact:

Prof. Dr. Alexandre Tkatchenko ([email protected])