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Field
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy
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. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
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development team Interacting with Continental business areas Developing and integrating AI algorithms into the real development progress Preparing academic publications such as patent applications and research
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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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and planning algorithm for high-speed autonomous vehicle. The work will involve algorithm development, simulation, test rig set-up, and experimental validation. Requirements: The candidate must at least
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- “Data-driven algorithms for multi-product inventory systems with non-stationary demand”. Qualifications Applicants should have:- (a) a doctoral degree, preferably in the area of operations management
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, leading and delivering innovative research to characterise and understand the search landscape and algorithm dynamics induced by combining complex optimisation problems and methods. Description of Duties
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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
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algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience