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We are inviting applications for a fully funded 3.5-year PhD Computer Science studentship at the University of Warwick, jointly supported by GlaxoSmithKline (GSK), to work on an ambitious project
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multispectral and/or SAR data to improve biomass recovery estimations, measuring biases between GEDI and EO time-series estimations, developing customised hybrid neural networks (e.g., CNN-LSTM for capturing both
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the above ‘Apply’ button. Under ‘campus’ please select *Loughborough* and select the programme ‘CDT Engineering Hydrogen Net Zero’. Please quote the advertised reference number *LU-EnerHy-2025-1* under
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demonstrate the utility of an adaptive mesh refinement approach in interface resolving Computational Fluid Dynamics (CFD) simulations of flow boiling at conditions relevant to nuclear thermal hydraulics
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biology, chemistry, psychology and social science, facilitating knowledge discovery. The intuitively uninterpretable high-dimensional data and network data become visually scrutable upon being mapped into 2
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engaging schedule of internal and external seminars. You will also have the opportunity to be part of the Scottish Graduate Programme in Economics (SGPE)—a collaborative network of eight leading Scottish
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programme, supervision by recognised experts, participation in network-wide workshops, summer schools, and conferences, secondments to industry and clinical environments. The candidate should have some
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complimentary computational studies to predict the intake aerodynamic characteristics and aid in the experiment design. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based
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High-Performance Computing is entering a revolutionary phase characterised by Exascale capabilities, with step-changes in technology enabling numerically intensive processes to answer outstanding
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to focus on the relationship between geometry and quantum theory. A key objective will be the conceptual and mathematical understanding of the original Penrose spin network, with a view toward foundational