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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission reduction, and social
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As a part of this collaborative research programme, you will join as one of three PhD candidates working on interconnected projects in Quantum Optimisation, People-Centred Design (PCD
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-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission reduction, and
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pilots utilizing advanced techniques at high-risk sites, including healthcare units and hospitals to remove pharmaceuticals at their source. The PhD topic will aim to operate and assess a pilot on
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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), sensing technologies (fiber-optic sensors, DIC), and computer science (machine learning tools). The aim of this Ph.D. project is to develop a novel bridge monitoring technique based on CLCE coating
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services