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, multidisciplinary research environment combining experimental surface physics, nanotechnology, and fluid dynamics. In return, we are looking for a candidate who has: A suitable academic background in physics
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and modelling techniques. Real-World Impact: Contribute to transformative technologies in clean energy and carbon capture. Future job opportunities: Digital modelling and computational fluid dynamics
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flows, and to have developed skills in experimental fluid mechanics, statistics, data processing, machine learning, and mathematical modelling. Supervisors: Dr Kostas Steiros Duration: 3.5 years. Funding
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networking, computing and sensing. Quantum technologies exploit the unique properties of quantum physics to deliver functionality that cannot be achieved using classical physics alone. A key challenge is the
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between things, developing the mathematical and computational foundations for optimal information transfer between surfaces and volumetric current distributions in complex scattering media. The research
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, Dr Eder Zavala, and Prof. Marcus Tindall Location: University of Reading, UK Duration: 3 years Start date: August 2026 at latest The students will be enrolled in the structured PhD programme at
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to understand these dynamics. This project proposes a novel pipeline of ideas to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses
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under uncertainty (Studentship code MSP106) Learning to sample: Meta-optimisation of gradient flows using reinforcement learning (Studentship code MSP107) Dynamic Bayesian modelling of endurance sports
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About the ProjectProject details Self-adaptive and autonomous systems are increasingly deployed in dynamic and uncertain environments, where effective decision-making relies on accurate models
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in the structured PhD programme at the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships