The consortium FAIRmat is building an International FAIR Data Infrastructure for Condensed-Matter Physics and the Chemical Physics of Solids: https://www.fair-di.eu/fairmat/

The enormous amounts of research data produced every day in the fields of Condensed-Matter Physics, Materials Science, and the Chemical Physics of Solids represent a gold mine of the 21st century. This gold mine is, however, of little value, if these data are not comprehensively characterized and made available. To refine this feedstock, i.e., turn data into knowledge and value, a FAIR (Findable, Accessible, Interoperable, and Re-usable) data infrastructure is a must. Only then, data can be readily shared and explored by data analytics and artificial-intelligence (AI) methods. Making data Findable and AI Ready will change the way how science is done today. The consortium FAIRmat sets out to make this happen.

FAIRmat is part of the international association FAIR-DI (https://www.fair-di.eu/). It starts from NOMAD (https://nomad-lab.eu/) but will significantly extend and advance these services by addressing materials synthesis, experiments, and theory and computations.

We are currently putting together an interdisciplinary team that is nearly complete by now. However, we are still looking for a computational materials scientists for Task 2: Excitations that is part of Area C, Theory and Computations. This Task is led by Roser Valenti (U Frankfurt) and Claudia Draxl (HU Berlin). We expect the successful candidate to have a strong background in excited-states methodology (many-body perturbation theory, dynamical mean-field theory, time-dependent density-functional theory) as well as excellent programming skills (preferredly Python).

This position is up to five years, even prolongation may be possible.

If you are interested, please apply at https://nomad-lab.eu/career/nomad-hub asap.