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within computational modelling, optimization and integration of thermal energy storage technologies – such as large water pits and phase change material storage. You will work with colleagues, and with
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: A master's degree in data science/AI, Mathematics, Electrical and Computer Engineering, or a related field. Strong background in machine learning, data science, and optimization theory. Desired
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Job Description We are looking for a PhD candidate to join the TACsy (Training Alliance for Computational Systems Chemistry) Marie-Skłodowska-Curie Joint Doctoral Network. This network consists
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integrated, holistic planning and scheduling to optimize resilience across several factory systems. Development of AI-based tools and complex simulation systems is expected to be a core contribution. 3) IT and
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researcher with a passion for developing new computational tools and contributing to cutting-edge research at the intersection of Physics and Earth system science. Background and relevance of the project
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, 107 Pd, 147 Pm, 151 Sm) from environmental samples (e.g. seawater, sediment, soil) and radioactive waste samples (e.g., spent resin, steel, concrete) Develop and optimize radiometric methods
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and estimate tidal components. When relevant, compare with tide gauge data. Develop robust station infrastructure capable of withstanding extreme Arctic weather conditions. Optimize power supply
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to survive transients without exceeding load limits; ▫ maximizing cut-out wind speed(s); Key aspects include observing & inferring usable flow field quantities via the AWES device; trajectory optimization
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institution that aims to contribute to the reaching of climate neutrality by 2050. The ambition of the SDU Climate Cluster is to create optimal conditions for ground-breaking, excellent, and interdisciplinary