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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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clearance level. The Engineering Doctorate Researcher will follow the EngD in Model-Based Systems Engineering Programme. They will be based at NPL. Entry requirements: A minimum of an upper-class honours
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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water basins across HMA. We will simulate future changes in temperature, precipitation, and snowmelt using climate projection models. These projections, combined with hydrological modelling, will allow us
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prostate cancer risk across diverse ethnic groups. This work aims to support more equitable risk stratification in cancer screening programmes. Using simulations based on multistate modelling framework
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perfusion as people age with various comorbidities (hypertension, hypotension, obesity) will preserve oxygen supply to the brain. MRI and two photon imaging are used in animal models to understand
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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-material capability with a suitable closure model; (2) improved strategy for interface tracking/capturing; (3) very high-speed scenarios with use of nonlinear Riemann-solvers. If time allows exploratory 3D