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Field
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to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated into smaller, faster, more energy efficient and cost-effective hardware
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computers”(under the UKRI Guarantee scheme). Topics include: Quantum many-body dynamics Quantum algorithms Quantum-enhanced numerical methods Quantum machine learning Tensor Networks Topological order The
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” and “wet” lab workflows). You will be able to Design, develop and implement algorithms and systems based on foundation models, large language models and/or AI agents for automated scientific discovery
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high dynamic range (HDR) imaging is redefining the way smartphone cameras and displays capture the world. Despite HDR becoming the new standard, many classic image-processing algorithms and generative
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. Based at Swansea University, you will play a central part in a multi-institution effort that blends algorithmic innovation with robust, production-quality research software. You will lead the design
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Regularization. We aim to develop mathematical understanding of implicit regularisation properties in deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical
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looking for researchers who can help design state-of-the-art swarm hardware for city deployments, cognition using edge-AI and perception, swarm algorithms for city-scale coordination, and interfaces
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simulations are plagued by the same slow relaxational dynamics. Through collaboration across Engineering, Statistics and Chemistry, this project will develop state-of-the-art simulation algorithms to circumvent
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are poised to re-define our future mobility. However, full autonomy is not possible without all-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms
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, memory, and energy requirements. The successful candidate will explore novel algorithms and model-design strategies that allow AI systems to operate effectively on edge devices, clinical environments