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, engineering, data science, and computer science. Skill Development: Our extensive qualification concept goes beyond research, offering targeted training in research methods, project management, and leadership
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Program if you aspire to an academic career. We offer you access to an international research network by presenting your research at leading international conferences and spending a research semester at top
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to challenging questions in the field of computational material design, especially with the help of CALPHAD-based methods. For further development of our simulation environment (https://github.com/cmatdesign
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Gesellschaftswissenschaften (Social Sciences) Course language English Financial support Yes Structured research and supervision Yes Research training / discussion Yes Support for international students and doctoral candidates
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(mechanical engineering, mechatronics, robotics, electrical engineering, computer science, etc.) -Know-How from lectures in robotics (e.g. environment perception, path and behavior planning, control) -Very good
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(mechanical engineering, mechatronics, robotics, electrical engineering, computer science, etc.) -Know-How from lectures in robotics (e.g. environment perception, path and behavior planning, control) -Very good
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extensive server infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer Science, Computational
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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 international
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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 systems with solid
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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, adversarial attacks, and