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Field
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following areas: mathematical optimisation, vehicle routing and scheduling, machine learning, reinforcement learning, logistics simulation, predictive analytics, or transport modelling. Strong programming
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under uncertainty. The role will suit a researcher with strong technical capability in quantum computing, data-driven modelling, infrastructure systems, computational optimisation, simulation
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manufacturing of wood-polymer composites (WPCs). The successful candidate will explore and optimise biodegradable WPCs and wood waste powder size and aspect ratio for use in extrusion and powder-bed fusion
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capability in quantum computing, data-driven modelling, infrastructure systems, computational optimisation, simulation, probabilistic methods, or related areas. This project is part of an ambitious research
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capability in quantum computing, data-driven modelling, infrastructure systems, computational optimisation, simulation, probabilistic methods, or related areas. This project is part of an ambitious research
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Campus Job Description About the job The role will execute day-to-day digital content production, manage social channels and calendars, coordinate programme marketing campaigns, and track basic performance
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algorithms, perception systems, digital twin simulations, optimisation frameworks, and autonomous decision-making capabilities for robotic systems involved in the handling, moving, and stacking of various
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Learning, and AI-driven robotic autonomy. The successful candidate will contribute to the development of intelligent software, AI algorithms, perception systems, digital twin simulations, optimisation
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samples, lack of training data and sample variability. In this project we aim to develop AI/ML workflows for improved quantitative analysis of LNPs. Your responsibilities will include optimisation of data
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We are seeking to hire a Research Assistant (Pre-Doc) to join the research group of Dr Giuliano Casale in the Department of Computing and the f-inference project. f-inference aims to shift from a