36 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "FEUP" scholarships at Aalborg University
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at the Copenhagen campus and one at the Aalborg campus. The themes cover key research areas of the department. Stipend no. 3: Data-driven methods for design and operation of human-centric energy-optimized indoor
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campus and one at the Aalborg campus. The themes cover key research areas of the department. Stipend: Synthetic Relighting of Real-World Environments via Generative AI and Computer Graphics Pipelines
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to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk ). CLASSIQUE will address a suite of fresh research challenges defined by
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. More information about DESS can be found at: https://www.cs.aau.dk/research/Data-Engineering-Science-and-Systems How to apply Your application must include the following: o Application, stating reasons
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Interaction venues. For further information about the project, see: https://www.nordforsk.org/projects/nordic-perspectives-collaborative-ai-blue-collar-work-cai-blue. Your competencies You must hold a master’s
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duration of the PhD research. Please see the RePIM project website (https://repimnetwork.eu/recruitment ) for further information. Qualification requirements PhD stipends are allocated to individuals who
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date. Candidates must be willing to move to Denmark for the duration of the PhD research. Please see the RePIM project website (https://repimnetwork.eu/recruitment/ ) for further information
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creativity and technology, and develops new areas in research and education directed towards the end-user. You can read more about the department here: https://www.create.aau.dk/om-create . How to apply Your
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technology, and develops new areas in research and education directed towards the end-user. You can read more about the department here: https://www.create.aau.dk/om-create . How to apply Your application must
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AI-driven creativity with clear environmental performance feedback early in the architectural design process. This phase is characterized by high uncertainty in data availability and design parameters