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contributions to standardisation efforts. Your role This fully funded PhD position focuses on exploring and developing hybrid quantum-classical algorithms to tackle sustainability challenges. Key areas include
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motors and braking technology, high-torque density axial flux electrical motors, development of servo controllers and algorithms, and special electrical machines such as superconducting electrical motors
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Your Job: Random unitaries are a ubiquitous tool in quantum information and quantum computing, with applications in the characterization of quantum hardware, quantum algorithms, quantum cryptography
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well as developing solution algorithms applying mathematical and computational approaches. The group has a particular focus on automated decision making in autonomous cyber-physical systems. Autonomous systems and
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novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
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technologies for medical diagnostics, treatment, and monitoring. Our research activities span computational modeling, algorithm development (using both traditional signal processing and machine learning
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of epigenetic changes to the DNA as biomarkers of biological age. Validation of Biological Age Biomarkers: validate a short-form of the assessments from Phase 2 and develop an AI model and algorithm-driven
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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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will design quantum-safe threshold encryption and/or authentication algorithms. The expected outcome is the design of methods, techniques and their software prototype to implement quantum-safe threshold
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(entities) given the rules and the rules given the molecules. The aim of this project is to develop a theory and accompanying algorithms to decide if an abstract system can be instantiated by a concrete