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interactions. Machine learning: reinforcement learning, or multi-agent systems. Signal processing: spectrum sensing, localization, or radio environment modelling. Multi-agent systems: distributed intelligence
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achieves shared goals and objectives. An in-depth knowledge of Supply Chain Analytics, including mathematical modelling, optimisation, and/or machine learning, and/or decision sciences. Advanced expertise in
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researching and implementing secure, AI-driven information systems and data analytics solutions using Python, R, and other advanced languages, with a strong focus on machine learning frameworks, generative AI
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This scholarship aims to develop practical methods for optimisaton in large supply chain operations. Ideally candidates should have strong AI, machine learning, and optimisation backgrounds
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that combine fairness, privacy and legal guarantees for ADM systems, such as recommender and machine learning based systems. It takes a multi-disciplinary approach and although focused on the mobilities and
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in implementing feasible blockchain-based solutions to support trustworthy machine learning. An opportunity for two talented students to undertake their PhDs on two projects that concentrate
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Join our multidisciplinary research team to develop and apply machine learning and bioinformatic algorithms in biomedical research. This PhD project will focus on developing machine learning
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. Proven track record of mentoring academic staff and managing academic teams. Qualifications Mandatory for Level C and Level D appointment: PhD in Electrical, Electronic Engineering, or a closely related
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below. Relevant Research Areas and Capabilities: Digital Engineering, Artificial Intelligence (AI) and Human Machine-Teaming Aerostructures and Flight Science Advanced Composite and Alloy Additive
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fairness, privacy and legal guarantees for ADM systems, such as recommender and machine learning based systems. It takes a multi-disciplinary approach and although focused on the transportation focus area