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passionate, curious, and driven individual, committed to accelerating the green transition by advancing autonomous solutions for wind power operations. You thrive on solving complex problems, ask bold and
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objective is to surpass the current traditional thermodynamic and optimization approaches, which are constrained in design discovery capabilities and long-term TES performance evaluation. Through your
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for optimizing metals microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM
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Job Description Are you driven by the idea of creating a more sustainable future through groundbreaking research? Do you want to work in a collaborative environment where your contributions can
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during training, an effect attributed to the properties of the optimization technique. Intuitively, stochastic optimizers tend to converge to flatter minima in the complex loss landscape, which is believed
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. Develop and apply state-of-the-art electron microscopy methods to study molecules-adsorbents interfaces. Collaborate closely with TUM to correlate nanoscale insights with material performance. Contribute
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on generating new knowledge for optimizing biological conversion of carbon dioxide to acetic acid in close collaboration with an industrial end-user of the developed technology. Responsibilities and tasks Your
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manufacturing platforms, data engineering, and AI-powered maintenance solutions—key capabilities for driving efficiency in the competitive semiconductor industry and beyond. You will explore how operational
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are looking for a passionate PhD candidate in Thermal Energy Systems with strong programming, optimization, and dynamic analysis of energy systems. This position is on the Horizon Europe-funded project