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Mixed-Integer Programming (MIP) solvers are very powerful tools to solve combinatorial problems that arise in many industries. Modern MIP solvers usually run a sequence of algorithms to solve
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Automated Program Repair (APR) is the grand challenge in software engineering research. Many APR methods have shown promising results in fixing bugs with minimal, or even no human intervention. Despite many studies introducing various APR techniques, much remains to be learned, however, about...
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package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
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guarantees of FL. In this project, we aim at an ambitious goal - designing secure and privacy-enhancing algorithms and framework for FL and applying our designs into real-world applications. To achieve
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. Building on its strong foundation in Optics and Photonics, EECS is expanding its research into quantum algorithms and their industrial applications. These new initiatives will be integrated into a state-wide
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with implementing these algorithms on fully error-corrected fault-tolerant quantum computers. About You The incumbent is expected to have relevant experience in developing quantum architectures, error
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to contemporary challenges while mentoring the next generation of leaders. Building on its strong foundation in Optics and Photonics, EECS is expanding its research into quantum algorithms and their industrial
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the appointment, and will have experience in asymptotic, algorithmic or probabilistic combinatorics, or a closely-related area. Applicants should also be active researchers with good written and oral
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Project (Next-Generation Solvers for Complex Microwave Engineering Problems). This project aims to design and develop physics-guided, data-driven algorithms that can accurately solve complex microwave
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algorithms formulating industrial problems to make them accessible to quantum algorithms mapping quantum algorithms to specific use cases and applications optimizing algorithms in the context of such use cases