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of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how
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close collaboration with the Technical University of Denmark (DTU), University of Toronto, Stanford University, and Utrecht University — research visits to partner facilities may form part of the position
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within battery state estimation, with a particular focus on emerging sodium-ion battery technology. You will be involved in both independent and collaborative research activities in close interaction with
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team working across electrolyzers, Power-to-X systems, power electronics, control, digital twins, and energy-system optimization, in close collaboration with the Technical University of Denmark (DTU
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presenting scientific results and demonstrated ability to drive a research project is highly valued. Collaboration and/or management skills: Ability to work effectively in collaborative, interdisciplinary
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within CFD modelling, with a particular focus on the projects MetNH3Energy and ACE Water. You will be involved in both independent and collaborative research activities in Europe in close interaction with
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spectrometry data, in collaboration with clinical microbiology at Aarhus University Hospital. Exploring novel MS data representations beyond binned spectra, such as audio spectrogram encodings or learned
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purification. The work will be in particular focused on the projects CYCLOPEM and You will be involved in both independent and collaborative research activities in close interaction with colleagues in the group
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employment This is a fixed-term position from 1 December 2026, or as soon as possible thereafter, ending 31 March 2028. Job description Conduct independent and collaborative research into the molecular and
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing