35 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" PhD positions 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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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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personalised media experience, as formulated in SMPTE ST 2110 suite of standards for video, audio and data over IP. This research asses the implications for public interest media of these fundamental changes and
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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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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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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