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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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needs. By bridging human-centric innovation, generative algorithms, and sustainability metrics, this project seeks to redefine how novel products and systems are conceived, developed, and evaluated. You
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" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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will develop autonomous on-board guidance algorithms for space missions using open-source numerical solvers for convex optimisation developed at the University of Oxford. The focus will be on designing
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format for the unambiguous and machine-readable characterization of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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experience in one or more of the following areas: machine learning, reinforcement learning, algorithmic trading, or data-driven modelling. Excellent communication skills: Solid written and verbal communication
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be finalised by July 2026. Supported Areas for START Engineering Energy Resilience: Power electronic converters for distributed energy resources and microgrids; High voltage DC transmission and
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optical setup construction. They will make use of commercial simulation software to test electromagnetic designs, algorithmic coding to design metamaterials, fabrication techniques to produce