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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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triboelectric nanogenerator (TENG) to sustainably power ingestible medical devices. The aim is to harness mechanical energy from natural intestinal peristalsis to enable battery-free operation of autonomous
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faculty in scholarly activities. Doctoral students also play an active role in the daily operation of the program. The study program features a three-stage structure with modules called “basis,” “workshop
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be placed on personal suitability, scientific reasoning, and the ability to write and understand scientific text. Basis of assessment The evaluation of the ability and potential to perform well is
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experiments and analysing data. Design and perform cultivation in bioreactors. Writing peer-reviewed scientific publications. Actively interacting and collaborating with other partners involved in the project
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that deliver high power density and exceptional efficiency at reasonable cost. However, most existing machines, particularly high-speed, radial-flux permanent magnet motors, are reaching their performance
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outstanding key performance indicators. Your tasks in detail: Contribute to develop an innovative process for the autothermal dehydrogenation of LOHC using fundamental knowledge of chemical engineering
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year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading