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, but it would be possible for those with mathematics, physics or other computational training to learn the healthcare context Experience in one or more of the following would be desirable: Programming in
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both homogenous and heterogenous catalytic conversion, including the handling, testing and characterizing the catalysts as well as the reactor and process simulation and analysis. Details will be
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October 2026 start ONLY For January and April starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme at
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Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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Research Assistant/Associate to undertake work as part of our NU Solve programme. Newcastle University Solve (NU Solve) in the School of Mathematics, Statistics & Physics (MSP) has a track record of
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on
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the goals of HEHTA, the Living Lab, and the Creative Communities programme. Co-create, build, and maintain a digital engagement platform in collaboration with stakeholders from government, healthcare
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on