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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
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, simulation of the vacuum conditions and heat management during operation, estimation of the pumping capacities including engineering of the pumping stations, gauges and valves, define the operating and system
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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
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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
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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
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data collection and metadata extraction protocols to enhance machine learning-based software applications for materials science. Your Profile: Master’s degree in Engineering, Computer Science, Physics
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/electronic engineering, computer science, computer engineering, physics, and related fields. For IC projects a strong electronics background, with experience in design and simulation of analog, digital
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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: Promotion Job description: Your Job: You will strengthen the data science and machine learning
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plant design is identified by considering the energy supply system, the choice of capture technology, the DAC-plant’s technical design, the DAC-plant’s operational concept and the positioning of the DAC
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, Energy Systems, or a related field of study Interest in Energy systems analysis, integration of renewable energy sources, grid resilience Good Knowledge in electrical networks analysis and simulations Good