Job announcements relevant to people interested in electronic structure calculations…
Due to the large number of posts recently, there is currently a delay of several weeks between posts being submitted and the corresponding emails being distributed to all users. Please bear with us while we try to improve this. In the meantime – and until this notice is removed – it would assist us considerably if you could submit only important and/or urgent posts and thus help to reduce the size of the mail queue. Under no circumstances should you resend posts multiple times when you find the emails are not distributed immediately.
In light of the Russian military offensive in Ukraine, we request that announcements relating to events, jobs and other activities associated with institutions supported by the Russian and Belarusian states are not posted to the Psi-k forum.
PhD: machine learning the electronic properties ... (No replies)
Back to Job listings...
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/).