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of solid-state matter to dynamic compression on nanosecond timescales. The academic standing of the Fellow, as an independent group leader, will be on a par with the other academics in the Department who
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different model sizes and deployment settings. Apply and advance model compression techniques, including quantization, pruning, knowledge distillation, low-rank adaptation, and related methods. Conduct
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Sensing (DAS) data processing and compression using ML Physics-driven machine learning for geophysical modeling and inversion Thus, the candidate is expected to have or about to have a PhD in a relevant
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energy-efficient cooling technologies for cryogenic temperatures (<70 K). At such low temperatures, conventional refrigeration technologies based on gas compression become inefficient or impractical, as
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simulation realism and by enforcing quantitative validation against helioseismic constraints. The project combines surface-cooling-driven convection, compressible fluid dynamics, and magnetic fields in ultra
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into a highly active research team with strong international visibility in image and video compression, learning-based coding, and multimedia signal processing. This project is funded by FCT/MECI through
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enforcing quantitative validation against helioseismic constraints. The project combines surface-cooling-driven convection, compressible fluid dynamics, and magnetic fields in ultra-high-resolution models
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based on gas compression become inefficient or impractical, as suitable compressible gases no longer exist and the required infrastructure becomes prohibitively complex and energy intensive. Solid-state
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develop new techniques for optimisation/modification of the laser pulse parameters, such as pulse focusing, filamentation, chirping, and temporal compression. Validate computational codes and implement
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We are looking for a researcher, whose expertise lies in Discontinuous Galerkin discretisations, compressible flows, and FEniCS/Firedrake/Dune, to work with Luis Espath & Prof Paul Houston jointly