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Field
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extreme scenarios. Your tasks: Conduct security and resilience studies for highly stressed systems (e.g., multiple faults, high renewable shares, or equipment failures). Evaluate system vulnerabilities and
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at https://www.slu.se/en/about-slu/work-at-slu/ Description: We are looking for a PhD to focus on separation of fat and proteins from dairy side streams and plant-based extracts. The project is a
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content
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doctoral training, interdisciplinary research, career development, and high quality research. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293904/phd-candidate-in
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Carl von Ossietzky University of Oldenburg • | Oldenburg Oldenburg, Niedersachsen | Germany | about 2 hours ago
on research fields, such as Neurosensory Science and Systems (University of Oldenburg) https://uol.de/en/phd-neurosensory-science-2 Auditory Sciences: Physics and Engineering, Physiology and Therapy of Hearing
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of a 5G base station for multiple devices and under different security configurations. Place of work: Place of work: The work will be developed at the premises of Instituto de Telecomunicações – Porto
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programme Yes Description/content The Institute of Development Research and Development Policy (IEE) at the Ruhr-Universität Bochum (RUB), Germany, offers an international and interdisciplinary three-year PhD
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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institutions, and a provider of research and development for companies throughout the world. The INM is an institute of the Leibniz Association and has about 250 employees. INM’s research group Immuno-Materials
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models