51 post-doc-image-engineering-computer-vision Postdoctoral positions at Technical University of Munich in Germany
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energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes
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per E-Mail mit dem Betreff „PostDoc application“ oder „PhD application“ an application@zachegroup.com . Ihre Bewerbung sollte folgende Unterlagen enthalten: • Motivationsschreiben (max. 1 Seite
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network with partners from science and industry and take on responsibility at the chair right from the start. In your role as a post-doc, you will combine team and institute-oriented tasks with in-depth
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agreement. The scientific employee (postdoc) will be employed on a 100% position at level E 14 TV-L (public sector pay scale). The post-doctoral researcher is expected to work in the area of entrepreneurship
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mathematics, computer science, information technology, electrical engineering, physics, mechanical engineering, or a comparable qualification Sound knowledge of mathematics and physics, especially in the fields
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. Requirements: Completed university degree in computer science or applied mathematics, remote sensing, geophysics, physics, or related areas Expertise in computer vision and/or machine learning (deep learning
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for students. Requirements We require for the position the following: A Ph.D. in the field of Applied Mathematics, Computer Science, Computational Science and Engineering, or similar. Knowledge of numerics as
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03.04.2024, Wissenschaftliches Personal Postdoc Green Hydrogen Financing (m / f / d) at the TUM School of Social Sciences and Technology, Professorship for Public Policy for the Green Transition
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on the Bildungscampus Heilbronn (Heilbronn Education Campus). TUM Campus Heilbronn focuses on the areas of managing digital transformation, family businesses, and computer science. Requirements - Master’s degree in
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
control of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human