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Field
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fingerprint identification (RFFI) for Wi-Fi. You will design novel RFFI algorithms and further evaluate their performance using practical testbeds such as software-defined radio platforms. You should have a PhD
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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work hands-on with clinical data and build robust deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image
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data to design robust, efficient deep learning algorithms that maximize the information extracted from images and delivered to the robot. To be successful in this role, we are looking for candidates
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, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing
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for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces
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service quality. To address these challenges, advanced methodologies and algorithms are needed to design effective revenue and inventory management strategies for complex stochastic systems. The growing
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teams to contribute to the development of fundamental aspects of computer science (models, languages, methods, algorithms) and to develop synergy between the conceptual, technological and societal
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conferences and journals. Overview: The successful candidate will join an interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific
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data analysis and modelling on this project. Specifically, advanced imaging processing skills, which will allow them to develop and validate algorithms for combination of multiparametric / multi-scale