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design A sustainable?”) represents a currently challenging research topic that warrants extensive exploration and discussion. This PhD project aims to pioneer a transformative approach to sustainable
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machine learning frameworks such as recurrent neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection
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neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection. Comparison with known analytic methods and
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Vertical Takeoff and Landing (eVTOL) Aircraft Technology for Public Services – A White Paper: NASA Transformative Vertical Flight Working Group 4 (TVF4)” https://ntrs.nasa.gov/citations/20205000636 Allahyari
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public-facing cultural programme. It offers the opportunity to develop a unique curatorial approach that engages with Gloucester’s civic transformation, supports the University’s strategic goals, and
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opportunity for an early-career researcher to contribute to transforming infection management in medical implants. Focused on addressing the challenges posed by implant-associated infections (IAIs), SHIELD aims
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the project is intended to inform the future design, delivery and evaluation of the Council’s Mental Wellbeing Transformation work aligned to its Progress in Unity Mission. The project will be led by Professor
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address Dr Chunwei Xia: c.xia@leeds.ac.uk Co-supervisor’s full name & email address Professor Zheng Wang: z.wang5@leeds.ac.uk Project summary Large Language Models (LLMs) have profoundly transformed the way
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of the covariance of physical laws under transformations between quantum reference frames. This is part of your personality: You have completed your Master's degree or Diploma in physics. You have experience in
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the University of Sheffield, and embark on this transformative PhD project! What You’ll Gain: Full PhD funding including tuition fees and a generous stipend Hands-on experience with world-class researchers and