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an important role in the efficient integration and management of solar energy in modern power systems. The studentship project aims to develop a novel PV forecasting model based on physics-informed neural
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Faculty of Environment, Science and Economy The above full-time (1.0FTE) post is available from early January 2026 on a 24-month fixed-term basis only, in the Department of Physics within
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. The successful applicant will support the research activities carried out by Dr Vinai and the project team, involving molecular dynamics simulation, support to laser processing of powders, physical
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sources of research funding and contribute to the process of securing funds and make presentations at conferences and other events. Applicants will possess a relevant PhD or equivalent qualification
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, where the default token-by-token prediction mechanism is slow and prone to "hallucinating" physically invalid configurations; and the prohibitive adaptation costs of fine-tuning billion-parameter models
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access to physical samples and observations, which are provided by PML and Marine Science Scotland. The student will receive training in elasmobranch taxonomy both from imagery and physical specimens
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that corrected pseudoranges correspond to physically consistent receiver positions across all satellites. Temporal smoothness: enforcing corrections that are consistent with expected receiver dynamics, such as
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The University of Exeter has a number of fully funded EPSRC (Engineering and Physical Sciences Research Council ) Doctoral Landscape Award (EPSRC DLA) studentships for 2026/27 entry. Students will
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
representations and embedding techniques that allow LLMs to natively interpret spectrum-related information, capturing the unique temporal, spatial, and physical characteristics of 6G signals. Building
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-making process. Research Objectives Model Learning in Dynamic Contexts Investigate the use of reinforcement learning for constructing and updating probabilistic world models (transition and observation