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-time sensing, multi-sensor fusion, and intelligent algorithms can jointly enable safer, greener, and smarter rail operations. Key research topics include eco-driving, environment cooperative perception
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, distributed ledgers) Desirable: Experience with generative AI (e.g. LLMs) Interest in Human-Computer Interaction Interest in privacy enhancing technologies (PETs) Other: Experience in presenting or preparing
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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1 and 2 and NQCC Testbed programme, will tailor the developed benchmarking approaches to error-corrected as well as distributed quantum computers, addressing the need for scalable benchmarks
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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the feasibility of using federated learning or distributed learning approaches to build and update device profiles without sharing raw traffic data. Furthermore, the system's ability to adapt to legitimate changes
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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allow you to explore the fundament physical limits of the technique and to create new image reconstruction algorithms. This project offers the opportunity to produce new techniques in imaging physics
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memorisation capabilities of deep learning models. Such vulnerabilities expose FL systems to various privacy attacks, making the study of privacy in distributed settings increasingly complex and vital
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public sources, data on the current status of ecological communities in several woodland patches across Wales, encompassing all taxa. The data will comprise species presence and distributions as