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Description The majority of hydrological models rely heavily on the principle of mass balance, often represented through Ordinary Differential Equations (ODEs). These models encapsulate
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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Exeter. Project Background: Sea lice increasingly threaten wild and farmed salmonid populations around the world, leading to substantial animal welfare concerns and economic losses. These ectoparasites
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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failure before components are built? We invite applications for a fully funded PhD project to develop microstructure-aware simulation models for fatigue and damage prediction in turbine wheels. Working in
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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this NWO summit EMBRACER project at the forefront of polar research. You will explore Arctic sea ice decline and ocean warming using satellite data and coupled modelling tools. Collaborate with
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(Kingdom of the) [map ] Subject Area: Advanced Nearest Neighbour Models for Active Matter Appl Deadline: 2025/09/10 11:59PM (posted 2025/07/14, listed until 2025/09/10) Position Description: Apply Position
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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') that aims to implement, evaluate, and scale-up novel Diabetes Footcare Hub models of care for people with diabetes foot disease living in regional and remote areas of Queensland. The model of care has