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or sensor arrays. Experience generating, processing and analysing large material property datasets including correlating between multiple techniques, or developing computational reconstruction techniques
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input, two key functionalities need to be developed: (1) the ability to physically manipulate material to perform polymerisations and (2) the ability to analyse and process data. Over the course of this
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physics and diagnostics at the York Plasma Institute Computational combustion modelling using High-Performance Computing (HPC) Machine learning techniques for predictive combustion models Research
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research programme funded by the Academy of Medical Sciences Springboard award. This project aims to explore the role of these neighbouring glycoproteins in neurotrophin-mediated neuronal development as
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undertake ground-breaking research in the fields of impact engineering, shock- physics, and materials science, involving elements of both experimental and computational physics. You will be based at Begbroke
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Award duration: 4 years Food processing currently relies heavily on the combustion of natural gas to provide process and space heating. Until recently, natural gas was considered the preferred fuel
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physical strain. With a suicide rate 3.7 times higher than the general population, the construction industry has become one of the most stressful and dangerous sectors, highlighting the urgent need
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model of particle physics can be tested, for example to help analyze experimental results from the LHC or the experiment to measure the properties of the muon at the Fermilab particle physics laboratory
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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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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can