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Field
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problems or machine learning more broadly. We are looking for candidates with strong mathematical skills and interests. A requirement for the position is a master’s degree in electrical engineering, computer
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(e.g. in machine learning, artificial intelligence, computer science, or a related discipline with an educational focus) Strong methodological research expertise in: Applying machine learning techniques
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Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent academic record, including
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it comes to running experiments an affinity to AI technology (incl. machine learning, computer vision) (German) permit to perform animal experiments (equivalent to FELASA B or C) desirable previous
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provide a dynamic environment which empowers excellence with state-of-the-art technologies, cutting edge infrastructure, and a global scientific network. Contribute your knowledge, vision, and dedication
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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assessment, programming and machine learning. If so, we encourage you to apply! You will develop exposure and physical vulnerability maps for past and future (1970-2100) and integrate these into a flood risk
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning Enthusiasm
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discipline Desirable: • very good programming skills • intensive up-to-date knowledge and experiences in computer vision or pattern recognition or applied mathematics • interests in cooperation with veterinary