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Learning, Algorithms, Noise Handling (Error Correction/Mitigation), and Verification. These roles are part of the Quantum Software Lab (QSL, link: https://www.quantumsoftwarelab.com ), in collaboration with
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development
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and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
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to numerical simulation algorithms? Then apply now to join our team of theoretical researchers in the Quantum Information and Quantum Many-Body Physics research group. Your personal sphere of play: As a
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. This can involve IoT connected devices, physical sensors or other instruments, including non-intrusive methods and inferences from a variety of data sources. You should have some experience with experimental
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real
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will deploy moored sensors (e.g. acoustic Doppler current profilers - ADCPs) in a series of submarine canyons in the Gulf of Mexico and along the US East Coast. Time-lapse bathymetric surveys and
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specialist knowledge and experience in data acquisition, signal processing, and data analysis from wearable or non-wearable sensors and devices. You must be able and willing to travel away from Oxford, often