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-to-design mapping, mixture density networks or MDN-based inverse generators will be employed to capture the multimodal distribution of the design space, enabling flexible inverse design sampling based
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one skeleton, but may leave many of tracks in their lifetime, often occur in stratigraphic levels where bone is rare, filling key gaps in the fossil record, and are more likely to be found in-situ
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. Changes in water table pre- and post-restoration will be monitored using the existing network of piezometers distributed across the floodplain and additional piezometers installed. Additional measurements
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theory and real-world applications, supporting the UK’s transition towards a renewable, inverter-based power system. The project is funded by Scottish and Southern Electricity Networks (SSEN) and you will
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Research theme: "Next Generation Wireless Networks", "Signal Processing", "Machine Learning" UK only How to apply: uom.link/pgr-apply-2425 This PhD project aims to design novel resource allocation
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real-world applications, supporting the UK’s transition towards a renewable, inverter-based power system. The project is funded by Scottish and Southern Electricity Networks (SSEN) and you will work
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University’s efforts to address this challenge by supporting development of an active network Design Tool for low voltage distribution networks. This tool is a key component of the flagship D-Suite project led
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, and providing world-class professional development and networking opportunities that strengthen both research outcomes and student success. The Computer Science group is part of the School of Computing
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Deadline: 30 September 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing
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Warwick: Prof. Zushu Li, Dr Zhiming Yan, Tata Steel UK: Dr Ciaran Martin, Dr Bin Xiao Start date: October 2025 (or earlier) Project Overview: An enthusiastic researcher is invited to join a team to work on