16 computer-science-programming-languages-"Prof"-"Helmholtz-Zentrum-Geesthacht" PhD positions at Technical University of Munich
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that are technically well-grounded and at the same time represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster
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project funded within the DFG Priority Programme “Illuminating Gene Functions in the Human Gut Microbiome” (SPP 2474) and be involved in microbiology and molecular microbiology of the gut microbiota
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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. Candidate´s profile: • Master’s degree in Life Sciences, in Computational Biology or MD degree • Previous research experience in immunology • Experience in flow cytometry, cell culture and in high-dimensional
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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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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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documents. Please send them by e-mail to marius.henkel@tum.de Technical University of Munich Prof. Dr.-Ing. Marius Henkel | Assistant Professorship of Cellular Agriculture | TUM School of Life Sciences Gregor
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teaching activities and/or supervise Master's students Requirements: A Master's degree (or equivalent) in Computer Science, Statistics, Mathematics, or related fields Strong programming skills (Python, Java
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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