PhD: Machine Learning the Electronic Properties of Metal-Organic Frameworks

We are looking for a highly motivated students with an interest in developing and applying machine learning methods to predict the electronic structure properties of certain families of metal-organic frameworks. The goal of the project is to discover novel materials that use external stimuli to efficiently adsorb and desorb gas.

Candidate should have a degree in physics, chemistry or related disciplines. Students with some experience in machine learning and/or ab initio simulations are encouraged to apply. A good knowledge of written and spoken English is essential to communicate with our external collaborators (US, Spain). The candidate should have some skills in programming languages (Fortran, C/C++, Python) and Linux.

To apply please send a full application before 20 May by email to Roberta Poloni (roberta.poloni@grenoble-inp.fr).

Applications should include: a concise but informative cover letter, CV, Master 1 and Master 2 (or equivalent) marks, names and contact of at least two references that can be contacted for recommendation letters.