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: Develop AI-assisted experimental workflows for oxide semiconductor deposition, aiming to accelerate process optimization and unravel new process–property relationships, and contributing to an EU Horizon
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on identifying suitable electrode materials and optimizing reaction conditions, electrolyte composition, and solvents, using three-electrode configurations and organic carbonate-based media. Building
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integration. Investigate how traction grids can support high-power charging at construction-sites though optimal sizing of chargers and mobile battery storage systems based on the demand and through energy
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though optimal sizing of chargers and mobile battery storage systems based on the demand and through energy management strategies under traction and AC grid constraints. Contribute to two pilots
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. The ideal candidate holds a PhD in transport, operations research, civil engineering, or a related field, with strong skills in mathematical optimization and modelling (ideally in Python) and an interest in
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engineering, or a related field, with strong skills in mathematical optimization and modelling (ideally in Python) and an interest in sustainable urban mobility. Job requirements PhD in OR and other related
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understanding with applied research and close collaboration with industrial partners, we develop solutions that contribute directly to the optimization of industrial-scale electrolyzers. More information about
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researcher, your responsibilities will include: Optimizing, and running head-fixed mouse behavioural tasks for harm-aversion and self-fear. Acquiring and analysing functional ultrasound imaging data from ACC
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experimental PhDs and Canon Production Printing to enable data-driven ink optimization. Why Join? Work in the multidisciplinary Processing and Performance of Materials group Work at the forefront of sustainable
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executed. In close collaboration with PhD researchers and project partners from TUM and ETH, you will contribute to the development of novel control and learning methods for aerial manipulators and multi