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Field
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waveguide setups and development of PCBs for reconfigurable intelligent surfaces (RIS).; 2. Implementation, testing, and optimization of RIS control algorithms on microcontroller-based platforms.; 3
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of a multi-modal dataset.; - Implementation of a software module for storing datasets according to a pre-defined standard.; - Development of routines for testing existing ML algorithms on a multimodal
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with applications to aerospace systems Designing, implementing, and testing control algorithms in simulation and hardware platforms Contributing to publications and reports; presenting research findings
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in algorithms development and refinement; (b) a good command of both written and spoken English; and (c) at least two first-authored publications. Preference will be given to those with: (a
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for autonomous driving. This project aims to advance the state of the art in visual perception algorithms and real-time systems for autonomous racing, pushing the boundaries of performance, speed, and precision
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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) optimise BIM software performance and address challenges, including model processing, data storage, and rendering efficiency; and (e) collaborate with AI algorithm teams to understand the business
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instructing or supervision of labs and tutorials. Prior teaching experience is preferred for candidates. It would be good if the candidate can also explore areas such as multimodal algorithms/techniques
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing