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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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academic supervision from Prof. Henkel. You will participate in the doctoral program of the TUM School of Management; after about a year, there is the possibility to apply for the School’s Academic Train-ing
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for food applications, through high-performance microbial bioprocesses (“precision fermentation”) and tissue-engineered cultured meat from animal cells. Requirements We are looking for applicants with a
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science technologies, and this is a perfect training opportunity for those who is interested in machine learning, data mining, artificial intelligence, and bioinformatics. High-performance computing may
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to suitability, performance and capability based on the German TV-L full-time scheme and is limited to 3 years. Contracting is in accordance with the German „Wissenschaftszeitvertragsgesetz“. Severely disabled
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Medicine (Director: Prof. Dr. Daniel Rueckert) is seeking to fill PhD candidate position (TV-L E13, 100% for 3 years) in Privacy-Preserving and Reliable Artificial Intelligence to be occupied starting from
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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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doctoral degree (Ph.D.). Remuneration is 100% TVL E13 according to the German public sector rates, resulting in a monthly rate of approx. €2,100 after tax. CMS’s inter-disciplinary team is performing
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interdisciplinary research team, focusing on human-robot interaction, unconventional robotics, cognitive systems and machine learning. You will have access to the full facilities of IDLab, including high-performance
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of the German Aerospace Center (DLR). For this international, exciting, and cutting-edge environment, we are looking for a PhD candidate on the topic of semantic understanding of the built environment using