74 assistant-professor-computer-science PhD positions at Technical University of Munich
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. Leonhardt) as part of the TUM Department of Life Science Systems. Starting date is fall 2025. The position is fixed-term (36 months). Salary scale: TV-L 13, 65%. As part of the assigned duties, there will be
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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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in Life Sciences or in Computational Biology • Experience in flow cytometry, cell culture and in high-dimensional single-cell data analysis and programming skills are a plus • Organizational skills and
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University Munich operates the high flux Neutron Source Heinz Maier-Leibnitz (FRM II) located at the science campus in Garching, Germany. The neutron source itself, its research instruments as
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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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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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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
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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