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A fully funded PhD position is available at the University of Groningen, the Netherlands. The PhD project focuses on utilizing control theory, optimization, and learning algorithms to design
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PhD in Intelligent Information & Incentive Design for Cyber-Physical Systems (V24.0341) « Back to the overview Job description A fully funded PhD position is available at the University of Groningen
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This PhD studentship is an exciting, fully funded opportunity to work as part of an internationally renowned scientific and engineering team to develop a new innovative technology to meet and overcome the serious challenges of increasing dissolved organic carbon (DOC) in the UK’s drinking water...
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PhD candidate, Compliance by Design: Technical Challenges of EU AI Act Requirements and Their Ethica
Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a: PhD candidate, Compliance by Design: Technical Challenges of EU AI Act Requirements
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Vacancies PhD position on Knowledge Representation & Responsible Design for Inclusive Employment Matching Algorithms Key takeaways This fully-funded, 4-year PhD research position is part of
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PhD Scholarship in Design optimizer tool and predictive control system of a Megawatt Charging System
deliver cutting-edge research, provide top-notch designs and developments on power electronics, powertrains and smart green energy solutions with intelligent control systems for tomorrow's mobility
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well as contribute to new knowledge, to join our team as a Doctoral Researcher. This PhD position presents a unique opportunity to engage in cutting-edge research focused on sustainable innovation in multinational
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at the interface between science frontiers and technological and medical applications. The project will suit an excellent student who enjoys design, practical experimental work, computer modelling and innovative
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part of Novo Nordisk Foundation Center for Protein Research (CPR ) and will later this year join the Biotech Research and Innovation Center (BRIC ), both of which are part of the Faculty of Health and
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Engineering research group, we are developing a digital twin of a proof-of-concept power plant, so that design can be carried out iteratively, considering the plant as a whole system. A key requirement for