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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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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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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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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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06.02.2024, Wissenschaftliches Personal The Livestock Systems research group at the TUM School of Science in Freising is recruiting a PhD student (m/f/d) to work on evaluating smart technologies
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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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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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world. The workflow spans from analytical chemistry to material science and engineering. There is no need for previous knowledge in the described fields but a strong motivation to learn and push the boundaries of our
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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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candidate, you have an outstanding Master's degree or comparable degree in biology, physics, applied mathematics or related disciplines. As an experimental candidate you have experience in biological systems