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Field
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contexts. They will be expected to contribute to the effective delivery of teaching, learning, and student support by: Delivering and evaluating classroom and practical teaching across modules Designing and
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, physical layer design, machine learning, and their applications to wireless communications. The successful candidate will also contribute to the formulation and submission of high-quality research
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projects, and grants and acting as a source of information and advice on best-practice methodologies in machine learning/deep learning. It is essential that you hold a PhD/DPhil (or close to completion) in a
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Machine learning for networks and systems Systems for machine learning Edge computing and applications Networked systems design and experimental evaluation Network measurement Network security Ability
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. Selection criteria: • Hold, or be near to completion of, a PhD/DPhil in biomaterials, bioengineering, biology, chemistry, nanotechnology, or related field • Experience establishing and
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, robotics, natural language processing, programming languages, AI, data science and machine learning. The School has an extensive portfolio of taught programmes, including the new MSc Computer Science
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first degree in an Engineering or Engineering-related subject and a PhD with appropriate content. Proven experience of experimentation and FEA modelling. Experience in some of the following areas will be
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. The post holder will join the Physical Mathematics Laboratory, a team of researchers led by Dr. Stuart Thomson with interests in physical applied mathematics, machine learning, and robotics. What will you be
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a package of support to enable you to develop a research career in this exciting field. PhD Topic: Federated Learning-based Intrusion Detection System for Intelligent Transportation Systems with Mixed
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and visualisation. Identify and establish best practices in the patient pathway and referral network through utilisation of descriptive analytics. Use predictive analytics and machine learning to drive