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to the success of the whole institution. The Faculty of Electrical and Computer Engineering the Institute of Semiconductors and Microsystems together with the German Cancer Research Center site Dresden, Division
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social challenges of Advanced Air Mobility (AAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly
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qualification program incorporating hybrid lectures, weekly seminars (hybrid and on-site), lab rotations and hands-on training annual summer/winter schools and complementary skills workshops TUD strives to employ
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qualification program incorporating hybrid lectures, weekly seminars (hybrid and on-site), lab rotations and hands-on training annual summer/winter schools and complementary skills workshops TUD strives to employ
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Transport. Within each of these fields, research programs are developed by our scientists and regularly evaluated by renowned international experts. Their evaluation forms the basis for the program-oriented
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interested in working at the boundaries of several research domains Master's degree in computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline
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. Applicants should have experience with tissue culture and standard molecular biology methods. Basic knowledge of computer programming (using the R software environment) and hands-on experience working with
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package including health insurance, pension plan, and family support services Access to infrastructure, equipment, and resources Opportunities for professional growth, networking, and international
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. At our location in
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning