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Nagaraj: M.Nagaraj@leeds.ac.uk Project summary Liquid crystals are ordered fluids which display birefringence and dielectric anisotropy. These properties allowed them to revolutionise display technologies
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), Cecilia Heyes (Oxford) and Phil Corlett (Yale). In this PhD studentship, you will lead on experimental and computational work looking at how social interaction biases feelings of confidence, and how
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missions such as search-and-rescue or large-scale surveillance—where environments are unknown, dynamic, and unstructured—robotic swarms must adapt, select appropriate actions, and respond to changing
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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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gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing
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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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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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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