375 programming-"Multiple"-"U"-"Prof"-"O.P"-"Humboldt-Stiftung-Foundation" "U.S" PhD positions in United Kingdom
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Field
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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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into practical performance solutions. The “Travel, sleep and fatigue optimal management for long-haul performance” PhD programme will focus on mitigating circadian and travel fatigue challenges associated with
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quantitative methods, prevention science and intervention studies. The postholder is expected to work collaboratively with other programme members spanning multiple academic and professional practice disciplines
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covers tuition fees, a stipend, and RTSG (research training and support grant). Alongside the scientific PhD training, the programme will provide a wide range of training opportunities. DTP Standard
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PhD Studentship: Multi-robot Cyber-physical Systems for Solar Farm Health Monitoring and Maintenance
of renewable energy infrastructure, including, but not limited to: Design and development of an adaptable and scalable Cyber-physical system comprising interconnected multiple mobile robotic platforms. Identify
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covers tuition fees, a stipend, and RTSG (research training and support grant). Alongside the scientific PhD training, the programme will provide a wide range of training opportunities. DTP Standard
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opportunities for embedding storage at multiple points within the HVDC architecture—on the AC side, DC side, or directly within converter submodules. The research will tackle several key technical, economic, and
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temperature stability and spatial resolution, to make a leap in this field. The PhD research programme will squarely address these challenges. The PhD candidate should have completed (or about to complete
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, and transport sectors (RENEW) Strong skills in implementing convex, linear, and mixed-integer programming and modelling frameworks (JuMP, Pyomo, Yalmip, GAMS, etc) Experience of working with future
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environments—such as fleets with multiple aircraft types. Objectives Objective 1: Map current data types, structures, and interoperability challenges to build a detailed "as-is" understanding of current