164 parallel-computing-numerical-methods positions at Technical University of Munich in Germany
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of Munich (www.cda.cit.tum.de ). Accordingly, we are currently searching for a Ph.D. Student to join our team to work on Design Methods for the European Train Control System! Our Research The European Train
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for Data Science in Earth Observation develops innovative methods for information extraction from remote sensing data in close cooperation with the Department EO Data Science of the Remote Sensing Technology
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and develop sample scenarios, roadmaps and trade-off analyses Develop software code and execute computational simulation Contribute to the design and development of an advanced test facility
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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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School of Engineering and Design and maintain strong links with the computer science community. One of our key research areas is the design and operation of intelligent networked production systems
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08.09.2021, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13
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Bioinformatics Position: The successful candidate will be a key member of an interdisciplinary team focused on the development and application of proteomic, metabolomic and bioinformatic methods to answer
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, simulation, and verification methods and software for emerging computing technologies. Our focus on interdisciplinary partnerships and networks will enable you to meet many interesting people (at places all
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The Professorship of Public Policy for the Green Transition (PPGT) focuses on designing and evaluating policies for the green transition worldwide. The group uses a variety of methods from automated data analyses
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of acquisition, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. We put emphasis on methods of distributed computing, machine learning, image and text