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multidisciplinary educational background, and possess a Master's degree in physics, physical chemistry, chemical engineering, materials science, nanoscience, mechanical engineering, or a closely related discipline.
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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History, General Literary Studies, Comparative Literary Studies, European Law, Protection of Industrial Property Rights, Patent Engineering, International Law, Private Law, Civil Law, Jurisprudence, Law
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of science, technology, and medicine. We welcome proposals with focus on regions around the globe and on any historical time period which can relate to and enrich the School’s research agenda. Please find all
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of potentially novel modes of protein binding is possible in collaboration with other members of the lab. Desired (but not absolutely required) skills: programming in python, machine learning, and experience in
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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, Engineering and Management, Materials Technology, Materials Sciences, Nanosciences, Nanotechnology Description Description Join a multidisciplinary research environment at Forschungszentrum Jülich to develop
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of science, education, culture, economics, society, technology and the environment. The school of Mechanical Engineering and Safety Engineering, Chair of Materials Science and Additive Manufacturing (head
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Artificial Intelligence) is being expanded into a leading German AI competence center for Big Data and Artificial Intelligence (AI). TUD Dresden University of Technology embodies a university culture that is