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substantial power demands, driven by the processing of vast amounts of data. As part of the ERC project H3PMAG, this project aims to address key challenges in power solutions for future AI demands, focusing
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oscillators with finite element methods (e.g. COMSOL). Elasticity theory. Open-quantum-system simulations with state-of-the-art analytical and numerical methods. Theoretical quantum optics. Scientific
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an LLM-assisted software framework for first-principles simulations, thereby gaining extensive experience within scientific software development and AI-driven workflow automation. The work will initially
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detailed CV (max 2 pages) Copy of certificates/diplomas (MA and PhD degree) A complete list of publications indicating which publications are most relevant for the position. The 3 most relevant publications
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important for this position. Please note that a copy of each publication must be attached as a pdf file. It is permitted to merge copies of the selected publications into a single PDF file. a teaching
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will collaborate with leading scientists and industrial partners to design and optimize next-generation solvent systems for energy-efficient carbon capture processes. Your overall focus will be
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identification and population monitoring Contribute to automated approaches for tracking long-term population trends in wildlife Collaborate with colleagues on ongoing modelling and simulation work across the
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on previous employment with start and end dates Copy of PhD certificate. If awaiting PhD, provide a written statement from the supervisor List of publications A description of your research interests in
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics
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following thematic areas: • AREA 1: Machine learning and AI-driven methods for design, simulation, and optimisation in architectural and construction engineering. • AREA 2: Robotic and additive