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Chemistry Materials Science Physics Computer Sciences Research Fellow, Research Assistant, Research Associate Baden-Wurttemberg Research Institute University

  • Academic Employee (f/m/d) in the area ofmachine learning for materials science and chemistry

    2021-08-20 Karlsruher Institut für Technologie (KIT) Eggenstein-Leopoldshafen Academic Employee (f/m/d) in the area ofmachine learning for materials science and chemistry - Karlsruher Institut für Technologie (KIT) - Logo
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Academic Employee (f/m/d) in the area ofmachine learning for materials science and chemistry

Published
2021-08-20
Application deadline
2021-10-15
Full-time position
Karlsruher Institut für Technologie (KIT)
Eggenstein-Leopoldshafen
Academic Employee (f/m/d) in the area ofmachine learning for materials science and chemistry - Karlsruher Institut für Technologie (KIT) - KIT - Logo
Karlsruhe Institute of Technology (KIT) – The Research University in the Helmholtz Association creates and imparts knowledge for the society and the environment. It is our goal to make significant contributions to mastering the global challenges of mankind in the fields of energy, mobility, and information. For this, more than 9.000 employees of KIT cooperate in a broad range of disciplines in research, academic education, and innovation.

We are looking for the Institute of Nanotechnology (INT) as soon as possible and limited for 2 years for a

Academic Employee (f/m/d) in the area of machine learning for materials science and chemistry


Your responsibilities involve the initialization of collaborations within the German-Canadian Materials Acceleration Center (GC-MAC) project. This includes independent planning and implementation of research projects in the area of artificial intelligence and machine learning applied to materials science, especially for energy materials. Research areas relevant to the project are regression models (e.g. graph neural networks) for materials property prediction, generative models for inverse material design, machine learning based material simulations, probabilistic models for autonomous experiments and similar areas. The application includes among others materials for hydrogen and CO2 electrocatalysis, membrane materials as well as battery materials. In addition to your scientific tasks, you will be actively involved in the GC-MAC project. This includes planning and implementatin as well as participation in (international) project meetings, tutorials and workshops.

You have a university degree in the field of materials science, physics, chemistry or computer science with a completed PhD and experience in the field of (energy) materials, materials simulations and machine learning methods, which you can demonstrate through relevant publications. Independent and creative work, strong collaboration and communication skills and a strong interest in interdisciplinary work are desired.

We offer you an attractive and modern workplace with access to the excellent equipment of the KIT, a varied work, a wide range of training opportunities and a casino/cafeteria.

We prefer to balance the number of employees (f/m/d). Therefore we kindly ask female applicants to apply for this job.

Recognized severely disabled persons will be preferred if they are equally qualified.

Please apply online until 15.10.2021 using the vacancy number 502/2021 and the reference number 6 to Ms Betül Kaya, Karlsruhe Institute of Technology (KIT), Human Resources, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany. For further information, please contact Prof. Friederich, E-Mail: pascal.friederich@kit.edu.

Processing of your personal data by Karlsruhe Institute of Technology (KIT) will be subject to this Privacy Policy.

You can find further information on the internet: www.kit.edu

KIT – The Research University in the Helmholtz Association
Academic Employee (f/m/d) in the area ofmachine learning for materials science and chemistry - Karlsruher Institut für Technologie (KIT) - Zertifikat

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