247 Education-"https:"-"https:"-"Universidade-do-Minho---ISISE" PhD positions in Netherlands
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Are you fascinated by how curiosity shapes learning in the classroom? Would you like to investigate how children seek information, explore and learn in real-world educational settings? If so, then we
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complex societal issues for a sustainable, healthy and just future. From forest fires to big data, from obesity to malnutrition, from helium to the universe and from genetics to medicine: our education and
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about biology and interested in building new machine learning and AI to accelerate biological discoveries? Then this position is for you! Join Us! We are looking for a motivated PhD candidate to develop
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morphology; analyse heat and mass transport phenomena during desublimation; develop or support modelling approaches that link experimental observations to predictive descriptions of the process; investigate
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assess the structural condition therefore enable both lighter designs and more efficient maintenance strategies. To address this challenge, the project aims to develop structural health monitoring
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of Political Science and the Centre for International Conflict Analysis and Management. As part of your PhD position, you will also contribute to teaching (max 5%) and will have the opportunity to work
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; develop or support modelling approaches that link experimental observations to predictive descriptions of the process; investigate the influence of operating conditions, gas composition, flow rate, pressure
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Are you fascinated by controlling magnetic matter by femtosecond laser pulses, eager to explore the underlying physical mechanisms, and passionate to develop a generic tool to ‘print’ complex
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. To address this challenge, the project aims to develop structural health monitoring technologies based on a digital twin. The digital twin will combine information from the physical structure with models and
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Can you help unlock the data needed for the energy transition? In the NWO-funded SHARE project, you will develop AI models that generate realistic, privacy-preserving synthetic energy data for grid