We look for highly motivated students with 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 May 20th by email to:

Roberta Poloni ([email protected])
Noel Jakse ([email protected])

Applications 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 joined for recommendation letters.

The PhD will be located in Grenoble and will be supervised by two researchers at SIMaP ((https://simap.grenoble-inp.fr/) and one researcher at LIG (https://www.liglab.fr/).