PhD: Machine Learning the Electronic Properties of Metal-Organic Frameworks
CNRS/SIMaP is looking to recruit a PhD: machine learning the electronic properties of metal-organic frameworks
- Closing date: 20 May 2021
- France | CNRS/SIMaP
- Date posted: 11 May 2021
- Job type: Academic: PhD/MSc
- Disciplines: Condensed matter | Materials science
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.
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