13 medical-physics scholarships at Newcastle University in United-States in United Kingdom
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(2024/25 UKRI rate), and a research training support grant of £20,000. Overview The PINZ CDT will train the next generation of process and chemical engineers, and chemists, to develop the new processes
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at Newcastle University. BVI Medical will provide a 3-month placement at their HQ in the US, and travel to international conferences to disseminate findings widely. Overview Do you have what it takes to do a PhD
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UKRI rate) Overview Interested in understanding the interplay between computer science and physics in the field of quantum technologies? Working in collaboration with various universities (Glasgow
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rate), and a research training support grant of £20,000. Overview The PINZ CDT will train the next generation of process and chemical engineers, and chemists, to develop the new processes, process
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future and embrace a circular economy framework. The process industries play a significant role in greenhouse gas emissions, making it crucial for them to adopt sustainable practices. This includes
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living allowance of £19,237 (2024/25 UKRI rate), and a research training support grant of £20,000. Overview The PINZ CDT will train the next generation of process and chemical engineers, and chemists
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a growing practical requirement for developing methods to represent these features explicitly in hydrodynamic models. This PhD project combines physical scale modelling with numerical modelling
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of visibility, scale, privacy, false-positives, and cooperation. AI based techniques will be explored to make Cyber Physical Systems forensic ready. Number Of Awards 1 Start Date September 2024 Award Duration 3.5
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Applications will remain open until we have filled our fully funded places. Sponsor Engineering and Physical Sciences Research Council (EPSRC) , Newcastle University, University of Nottingham and Industrial
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. Strong programming skills, preferably Python, Matlab, or R. Experience with one or more of hardware-programming, cyber physical/electrical systems, privacy-enhancing technologies, machine learning, signal