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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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defects. The charge transport will be implemented stochastically to mimic nature. A significant focus of the project will be to apply machine learning techniques to optimize the model and enable charge
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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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, graph theory, satisfiability problems, discrete optimization. Strong interests in chemistry as well as proven competences in programming and ease with formal thinking are a necessity. This PhD project is
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processing, optimization, or information theory; Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is a plus; Familiarity with the basic concepts
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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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, graph theory, satisfiability problems, discrete optimization. Strong interests in chemistry as well as proven competences in programming and ease with formal thinking are a necessity. This PhD project is
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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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footage. You will process and annotate large-scale EM datasets, collaborating with fisheries scientists to ensure accurate species identification. A key task will be to optimize and validate algorithms
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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