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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory
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qualification program for PhD students containing excellent multidisciplinary training with tailor-made subject-based and soft skills courses, annual retreats, summer school, and a supervision concept. More
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are necessary to complete the task. If you hold a diploma or Master's degree in Computer Science or Engineering, possess a sound knowledge of applied informatics and want to join a highly motivated research group
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modelling is greatly beneficial. Excellent English and the willingness to learn the German language are necessary to complete the task. If you hold a diploma or Master's degree in Computer Science
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and an extensive server infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer Science
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networks and their demonstration as proof-of-concept implementation in an experimental 6G testbed. Your qualifications MSc in Computer Science or Electrical Engineering Strong background in networking and
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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the developed code Publishing the developed approaches in international journals and conferences Requirements Promising applicants have: A master’s degree in Computer Science, Geodesy, or related discipline Very
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or comparable degree in biology, physics or a related discipline. You have experience in quantitative biology, experimental soft matter, or experimental biophysics. You enjoy working in interdisciplinary and