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Field
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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will
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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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of Applied Psychology . Current faculty conduct research on a wide range of topics pertaining to the future of work, including entrepreneurship, collaboration, remote working, labor markets, algorithms
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algorithms, models, and techniques. - Perform rigorous benchmarking and evaluation of the developed models. - Optimize algorithms for efficiency and scalability. Collaboration & Mentorship - Work closely with
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generation of enhancement algorithms tailored for endoscopic videos, with a focus on applications in real-time interventions. Development efforts will prioritize both enhancement quality and computational
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Location: Odense, 5230, Denmark [map ] Subject Areas: Pure math, with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. Appl Deadline: 2025/12/01 11
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Khani. Job Duties: Developing new models, optimization algorithms, and machine learning algorithms for transportation systems and services (40%). Applying the models and algorithms to new transportation
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(essential) / PhD (desirable) in Computer Science, AI, or a related field. Essential skills/ experience required include: Strong Understanding of machine learning algorithms, including deep and federation
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in Quantum Mathematics with emphasis on pure mathematics with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. The targeted starting date
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Quantum Mathematics with emphasis on pure mathematics with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. The targeted starting date