673 postdoctoral-image-processing-in-computer-science-"EPIC" PhD positions in United Kingdom
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this multidisciplinary project, the student will develop expertise in: Direct collaboration with leading medical imaging and materials science partners. Access to Cranfield’s advanced materials characterisation and
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) publication at top tier ranked international conferences and journals in Computer Science. Person specification: MSc in Computer Science or AI (minimum of 2:1 degree or higher) UK home student status holder
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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Department of Chemistry Funded PhDs Funded opportunities to work on specific research projects in a variety of areas across the Department of Chemistry. Eligibility: PGR applicants in the Department
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co-supervised by both academic and industry experts, gaining valuable skills at the interface of hydrogeology, environmental engineering, and computational modeling. Research Objectives (1
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(e.g., in the context of risk, uncertainty, future thinking), social processes (e.g., interpersonal dynamics, social norms, and influence), and behavioral outcomes (e.g., behavior change, social action
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with mechanical testing of the alloys in hydrogen rich environments will be used. The ReNU+ CDT has hosted a number of online pre-application workshops to provide guidance on the application process
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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rate). An additional allowance will be provided to contribute towards consumables, equipment, and travel related to the project. Number Of Awards ReNU+ is a unique and ambitious programme that will
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the PhD student in high-performance computing, computer programming, applied mathematics, fluid mechanics, mathematical modelling and data analysis for large datasets -of the order of 100 Terabytes