71 fully-funded-phd-program-computer-science-eth PhD positions at Technical University of Munich
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21.12.2021, Wissenschaftliches Personal The Department of Computer Science, Technical University of Munich, has a vacancy for a PhD candidate/researcher position in the area of efficient algorithms
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degree in a technical field (mechanical engineering, mechatronics, robotics, electrical engineering, computer science, etc.) -Know-How from lectures in robotics (e.g. environment perception, path and
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polycephalum arises from the interactions of cell nuclei within its gigantic cell. We are looking for a PhD student (m/f/d) to start at the TUM this summer or fall. Your Task The network-forming slime mould
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21.10.2021, Wissenschaftliches Personal PhD Position at TUM Department of Science, Technology & Society (65% for 3 years) within a DFG-funded research project led by Dr. Susanne Koch and affiliated
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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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degree (Ph.D.). IGSSE grants a fully funded scholarship (€ 2,000 monthly), including a competent international qualification program. The scholarship is for four years provided that the progress
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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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technical field (mechanical engineering, mechatronics, robotics, electrical engineering, computer science, etc.) -Know-How from lectures in robotics (e.g. environment perception, path and behavior planning
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Master’s degree in biotechnology, bioengineering, bioeconomy cell biology, molecular biology, or a comparable field of study, preferably with a background in life cycle assessment (LCA) and techno-economic