We are searching for up to two postdoctoral researchers (full-time or part-time, 2 years) for a computational materials screening project in collaboration with a large industrial company. The tools of choice will be high-throughput screening using density-functional theory, supported by machine learning. The research context is in the area of semiconductors, specifically the determination of properties for energy applications such as batteries, photovoltaics or thermo-electrics. The work will be performed at Ghent University, in the research group of the Material Science and Technology and the Center for Molecular Modeling. These positions are particularly relevant for researchers who have a career in industrial R&D in mind or who want to build experience in that area. You will have access to the computing resources of the VSC (Flemish Supercomputing Center, vscentrum.be).

The ideal candidate(s) have a PhD in physics, chemistry, materials engineering, engineering physics, chemical engineering or related areas. You are an experienced user of DFT codes (VASP) and you can set up and run high-throughput studies using the proper tools to handle workflows for a large number of crystals. The physics of semiconductors is familiar to you. Knowledge about machine learning methods using Python – such as DFT-based potentials, property prediction models or as a means to speed up high-throughput studies – is an asset. You are comfortable working in high performance computing environments. When selected, you are available to take up this position in the immediate  future.

The starting date is as soon as possible.

Informal inquiries can be sent to [email protected]. Formal applications must be done via https://www.ugent.be/en/work/research-staff, until October 17.