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Field
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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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) for performing fundamental research in the frame of the project AI-CHECK funded by the International Graduate School of Science and Engineering (IGSSE). The candidate has the opportunity to pursue a doctoral
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infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer Science or a similar field Good theoretical
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available in the further tabs (e.g. “Application requirements”). Programme Description Early-career scientists from all countries of origin and any subject carrying out further research work into the field
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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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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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fundamental knowledge about the handling and capturing of flow behavior in multistage compressors. The collaborative frame with a prestigious industry partner will give insight to future technology requirements
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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
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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