22 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"TCAT-Dickson" positions at University of Warwick
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- See advert for details Deadline: 13 April 2026 Supervisors: Dr Subhash Lakshminarayana (Lead) and Dr Michael Faulkner Safeguarding Power Grid Stability in the Age of Artificial Intelligence (AI) Data
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of pre-eclampsia Research area and project description: Pre-eclampsia affects 1 in 10 pregnancies, yet diagnosis remains uncertain. This PhD will integrate clinical data and blood biomarkers to improve
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and hence open to UK nationals and those of equivalent status. [More information here ]. Applicants that do not meet UK home fees requirements are also encouraged to apply for this position, however
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reliable transmission of demanding multi-modal data such as haptic feedback, video, and 3D sensing data. This project will develop AI-driven predictive network intelligence to anticipate delay and network
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-effort services rather than guaranteed real-time performance, and the transmission of multi-modal data streams in telesurgery—such as point clouds, haptic feedback, and audiovisual signals—places
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of spins that could form the basis of future low-power data storage devices. However, real skyrmions are three-dimensional and can twist, stretch, or deform when trapped by material defects - behaviour
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receive comprehensive training in synthesis, analytical measurements, computation, data analysis, and catalysis. They will be fully integrated into research groups at both Warwick and VUB and will benefit
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a combination of synthesis, analytical measurements, computation, data analysis, and catalysis. They will be fully integrated into the research group and will benefit from extensive transferable
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physics-based and data-driven methods to support the design and scale-up of these systems. This approach will reduce the need for costly experiments, improve scale-up predictions, and provide confidence
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PhD Studentship: Bottom-up Decoding of Protein Conformational Landscapes: from Gas-phase to Solution
folding simulations with mass spectrometry experimental data, creating a unique multi-stranded methodology to map out free energy landscapes associated with protein folding in environments spanning gas