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The MARIS Lab in the School of Civil and Environmental Engineering (Maritime Studies Program) at Nanyang Technological University (NTU), Singapore invites applications for a PhD position starting
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domains, including architecture, anthropology, arts and culture, computer science, history, literature, linguistics, management, and more. Selected candidates will be enrolled in PhD programmes under joint
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architectural design, urban planning, building technology, social sciences, process management, and geo-information science. The faculty works closely with other faculties, universities, private parties, and the
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PhD Project in Outdoor Recreation and Green Space Planning Department of Geosciences and Natural Resource Management Faculty of Science University of Copenhagen The section of Landscape Architecture
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PhD studentship in Trustworthy Multimodal AI under Lightweight and Data-Efficient Architectures Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
such a promising technology, the centralised and resource-intensive nature of current LLMs conflicts with the constraints of aerial 6G networks in terms of limited computation, energy, and communication
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architecture, anthropology, arts and culture, computer science, history, literature, linguistics, management, and more. Selected candidates will be enrolled in PhD programmes under joint supervision, awarding a
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on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions. According to the Ministerial Order, the progress of the PhD student shall be assessed at regular points in time
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 3 days ago
devices will be able to perform computation and communication with energy harvested from the environment and from ambient wireless signals. The PhD student will be part of the design and electronic
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private. This PhD will focus on three strands of work: 1) Innovate NILM model structures. Design efficient neural network architectures for both aggregator and client models that meet strict accuracy