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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
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of Power-to-X processes for renewable fuel production. The project is primarily rooted in process engineering while also addressing the interaction between Power-to-X plants and the electrical grid. You will
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the ambition of producing contributions relevant to leading venues in both the communications and AI communities. Your competencies We are looking for a candidate with a Master's degree in electrical engineering
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provides additional context for the assessment. However, this is not a requirement. Framework for the PhD Programme The PhD programme is conducted in accordance with the current Danish Ministerial Order on
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, deterministic systems. You model them, you optimize them, you operate them. That paradigm is breaking down. As electricity replaces fossil fuels, industrial systems must operate under fundamentally new conditions
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of hydrographic and current measurements obtained using CTDs, ADCPs, moorings, and related observational platforms. • Experience in analysing large oceanographic and climate datasets, including observational and
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the general study programme Electrical and Electronic Engineering; as per September 1, 2026, or as soon as possible thereafter. In electronic engineering, Aalborg University is known worldwide for its high
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Sustainable Power Electronics and Electrification Research Group at the Department of Energy Technology. Cyber-Physical Energy Systems, such as electric vehicle chargers and power grids are increasingly exposed
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, naval architecture, mechatronics, electrical engineering or similar. The ideal candidate will have skills such as: Marine systems and propulsion: Knowledge of marine propulsion, hydrodynamics, ship
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Generative Artificial Intelligence (GAI) is rapidly transforming higher education, yet most current GAI systems are designed to support individual productivity rather than collaborative learning