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Interacting dark energy models in light of cosmological data School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof Carsten van de Bruck Application Deadline
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models of the additive manufacturing process. Surrogate models to accelerate virtual material testing and verification will be developed to allow the generation of property distributions from process
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Award at the University of Sheffield. We aim to develop retrieval-augmented, multi-modal, and explainable Large Language Models (LLMs) for healthcare fact-checking. Reliable healthcare information is
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field measurements and building energy-thermal modelling, assists developing the preliminary Heat Vulnerability Index and assessing intervention feasibility, and supports transdisciplinary team
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, with important consequences for host outcome. You will use a range of cutting-edge in vitro and in vivo models of bacterial infection to: Assess the effect of deficient type I IFN responses on disease
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immune cells to sterile wounds and mycobacteria is also impaired. We will use a range of in vivo and in vitro models to: 1. Evaluate systems level effects of deficient and enhanced JAK-STAT signalling by
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” of geometry, similar to how a fluid fundamentally consists of atoms and molecules. Simple models of cosmology can be derived from the collective behaviour of many such atoms and agree with what we expect
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Advancing Human Motion Understanding through 3D Modelling and Foundation Models (S3.5-COM-ZChen) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr Zhixiang
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safer, more reliable, and more transparent. It has two main goals: First, the project will create new ways to automatically test and check the code produced by language models. This includes designing
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require the use of cognitive shortcuts. - To develop and fit computational models (e.g., reinforcement learning, Bayesian models) to participant data, allowing for a precise, quantitative definition of