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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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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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Computing (e.g., memristor modeling/simulation/manufacturing) and Edge AI related areas (e.g., AI algorithms, AI accelerator, VLSI). Background Investigation Statement: Prior to hiring, the final candidate(s
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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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imaging phantom-based evaluation of quantitative SPECT/CT; reconstruction algorithm development; establishing a secondary standards laboratory for unsealed source metrology through gamma spectrometry
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Predictive Control (MPC) algorithms, innovative coalition-formation techniques, and validate these through high-fidelity simulations. You will design, implement and validate innovative data-driven economic
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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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
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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
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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and