-
include: Researching, in particular, publicly available data on current and future materials for energy technologies Implementing the materials in our technology database and in our energy system model
-
substitution options within the energy system Implementing the phased-out material flows and their substitution options in our technology database and in our energy system model ETHOS.FINE Deriving demand
-
to the FAIR-ification of data, establishing systematic data collection and metadata extraction protocols to enhance machine learning-based software applications for materials science. Your Profile: Master’s
-
and develops a wide range of topics related to chemical hydrogen storage along the entire process chain. We place a particular emphasis on LOHC technology, addressing issues across different scales. Our
-
machine learning-based software applications for materials science Develop code and utilize machine learning to support the automation of characterization and fabrication processes Ensure the integration
-
information from experiment data Evaluation and development of specialized and/or interpretable machine learning approaches for the domain of materials science, physics, microscopy Incorporation of machine
-
preparation Deriving insights for film and device fabrication based on the above described workflow Your Profile: Masters degree in physics, materials science, physical chemistry, electrical engineering and
-
Your Job: The electrocatalytic interface engineering department led by Prof. Dr.-Ing. Simon Thiele focuses on synthesis, manufacturing, analysis and simulation of functional materials to find
-
Your Job: Nanoporous materials are key components in electrochemical hydrogen technologies, most importantly in the form of electrocatalytic layers (ECLs) of fuel cells and electrolysers
-
Profile: Master’s degree in Materials Sciences, Chemistry, Physics, Radiochemistry or a related discipline Experience or interest in nuclear energy, waste management, nuclear fuel or spent nuclear fuel