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management, writing, networking, and career advice and coaching. Course organisation The PhD training programme combines mandatory elements required for all doctoral candidates within GEAS with methods and
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Research Foundation (DFG) – offers a three-year, English-language doctoral programme with a highly complex, multidisciplinary field of research that provides our doctoral candidates with an outstanding
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interdisciplinary projects, e.g., in economathematics, mathematical physics, and mathematical data science Internationality and cooperation – enhancing students' ability to work in international networks and
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possible to understand complex processes in tissues and organs. At the same time, it also allows new knowledge to be gained about diseases. The sonogenetic technologies will also be used to establish new
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Master Thesis on Bayesian Optimization of Multi-stage Processes with Smart Inducing Point Allocation
, intermediate outputs). This information is highly valuable but not easy to use. With our research we have developed probabilistic methods, which we call Partially Observable Gaussian Process Network (POGPN
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, intermediate outputs). This information is highly valuable but not easy to use. With our research we have developed probabilistic methods, which we call Partially Observable Gaussian Process Network (POGPN
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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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the manufacturing of customer-specific solutions and prototypes. The department »Opto-mechatronical Components and Systems« develops technologies for assembling and integrating complex, miniaturized and highly
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domain are inherited by biometric systems. Such challenges are related to miniature deep learning networks, explainable decisions, and domain adaption. Our team is offering several open thesis positions
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products and processes. The Competence Center »Energy Management and Control« develops innovative solutions for the economically and technically optimal operation of highly complex energy systems. We develop