220 computer-programmer-"https:"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "Dr" "P" positions at Technical University of Munich
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. Experience in programming (in particular, Python) and an interest in machine learning, data analysis, or scientific computing are expected. Prior experience with machine learning or optimization methods is
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on a dynamic project, we encourage you to apply. Contact: Prof. Dr. Marc Schmidt-Supprian marc.supprian@tum.de Tel.: 089-4140-4104 Klinikum rechts der Isar Technische Universität München TranslaTUM
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computer science, electrical or mechanical engineering, applied mathematics, or a similar engineering-oriented quantitative discipline Advanced software development and data analytics skills Hands-on mentality with
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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technologies and develop algorithms and software tools dedicated to accelerating research on multiple levels. We are working at the intersection of computer science, physics, and material science to push the
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10.01.2022, Academic staff The Chair of Computational Modeling and Simulation (CMS) at Technical University Munich invites applications for the position of a Research Assistant (m/f/d
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the same qualifications. For further information, please contact Dr. Regina Wanschura and Dr. Elisabeth Windeisen-Holzhauser. The position is suitable for disabled persons. Disabled applicants will be given
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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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26.07.2023, Academic staff The Professorship for Cellular Agriculture (Prof. Dr.-Ing. Marius Henkel) was established in September 2022. Cellular agriculture is a multidisciplinary field that
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automate crucial design steps. In addition, we are developing simulators (on various abstraction levels; using, e.g., Computational Fluid Dynamics) which enables us to validate designs of microfluidic