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Information Benefits As a PhD candidate at UT, you will be appointed to a full-time position for four years, with a qualifier in the first year, within a very stimulating and exciting scientific environment
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to benefit the teaching and learning of mathematics. FERMAT has made streamlining assessment one of its core interests. We seek a PhD candidate who is passionate about mathematics education to engage in a
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PhD position Facilitating the co-creation of sponge measures and strategies in European river basins
basin strategies to practical action perspectives. To address this challenge, this fully funded PhD position aims to develop approaches for inclusive, integrative and effective co-creation and knowledge
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related to staff position within a Research Infrastructure? No Offer Description The four-year PhD position starts on the 2nd of September 2024 (or as soon as possible thereafter). The research project will
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industry partners. The successful candidate will be embedded in the DMB research group, and the supervision will be ensured by Dr. Elena Mocanu and Prof. dr. Maurice van Keulen. This PhD position is part of
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highly motivated PhD candidate to research on the topic of friction mechanisms in single-grain sliding. The challenge Under highly accelerated slip, several physical phenomena contribute to the dynamic
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available1Company/InstituteUniversiteit TwenteCountryNetherlandsCityEnschedePostal Code7522NBStreetDrienerlolaan 5Geofield Where to apply Website https://www.academictransfer.com/en/339874/phd-position-in-machine
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related to staff position within a Research Infrastructure? No Offer Description The Faculty of Behavioural, Management, and Social Sciences at the University of Twente is currently seeking a PhD-student
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://www.academictransfer.com/en/339450/phd-position-reinforcement-learning-… Contact City Enschede Website http://www.universiteittwente.nl/ Street Drienerlolaan 5 Postal Code 7522 NB STATUS: EXPIRED
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to staff position within a Research Infrastructure? No Offer Description The main goals of this PhD project are: Develop novel sparse training algorithms that improve the scalability and energy