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informative but also pose significant privacy risks. Your work will focus on developing and studying privacy-preserving methods, such as differential privacy, Bayesian privacy, federated learning and synthetic
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implementation or comparable tools. Experience with one or more relevant methods, such as multi-objective optimization, model predictive control, mixed-integer optimization, stochastic optimization, energy
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ability to conduct independent scientific research Strong methodological competence in qualitative or ethnographic research methods a track record or clear potential for publishing in international peer
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is clearly connected to Deep Learning and Computer Vision, and you can demonstrate experience with semantic segmentation, object detection, and generative AI models. You have solid skills in
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should have the following qualifications: Ph. D. degree in data science, electrical engineering, computer engineering, computer science, mathematical engineering, or similar. Proven track record in
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industrial specialisation, medicine, and more. You will thus be joining an inspiring, enriching, and productive cross-disciplinary research centre including staff with internationally recognised track records