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Collaborative EPSRC Doctoral Landscape Award. Qualification: Doctor of Philosophy in Engineering (PhD) Eligibility: UK Students Award value: Tuition fees and tax-free stipend - See advert for
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Degree PhD – Dr rer nat Doctoral degree or degree awarded by Ludwig Maximilians University of Munich or Technical University of Munich Course location München In cooperation with LMU Munich, Max
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expertise in HCI and education, including adaptive gamification, engagement, learning analysis, and the design of motivational affordances in education. As part of the project, the PhD student will work with
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cities in the project will make a lasting societal impact. The PhD research will involve actual applications, enabling you to really make a change in people’s life. In the Netherlands, the municipality
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poorly understood. This PhD project addresses that gap. Sitting at the intersection of clinical simulation, multimodal AI, and human factors research, the successful candidate will design high-fidelity ICU
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Application deadline: 30/04/2026 Research theme: Nuclear Engineering How to apply: https://uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded; home students are eligible to apply
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companies. The Department of Design is one of four departments in the Faculty of Architecture and Design . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/297392/phd-candidate-in
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the supervisor’s complimentary research expertise in this area (https://millerresearchgroup.co.uk & https://www.lovelockresearchgroup.co.uk),[8,9 ] this PhD will involve the design and chemoenzymatic synthesis of a
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 9 hours ago
your career. We now seek a highly qualified and motivated PhD student (f/m/x) to drive the development of a novel quantum enhanced microscope. Your tasks Design and engineer a next-generation microscope
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seeking a PhD candidate in computer architecture. The research focus of this PhD position is the design of performant and energy-efficient Edge Artificial Intelligence (AI) accelerators. Such accelerators