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within deep learning, big-data, computer vision, or related fields, as well as experience in in-line process monitoring or similar areas. Preference will be given to candidates with competence in concrete
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electroluminescence and photoluminescence imaging, preferably daylight and field-based methods. Proven skills in data analysis, image processing and machine learning. Experience with PV performance modelling, power
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requirements, including link budgets, beam steering, and orbital pointing dynamics. • Experience with optimization methods and physics-informed machine learning. • A strong publication record in antennas
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for spinal surgery. The Candidates for this stipend should have a background in software engineering or similar and have substantial experience with machine learning. All cases involve various degrees of image
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, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system-level programming, developing prototype