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a Research Fellow to contribute to a project focused on algorithm design in Game Theory and Fair Division. Key Responsibilities: Formulate mathematical models for research problems in computational
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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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the requirements of distributed LLM inference at collaborative edge environment; (b) design the system model of collaborative edge AI for distributed LLM inference; (c) design algorithms and
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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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binding pockets. About the role We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to identify domain functional families
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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algorithms that integrate general and domain-specific knowledge with data. By combining the mathematical and computational cultures, and the methodologies of statistics, logic and machine learning in unique
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or use existing simulation platforms to validate the developed algorithms and models. Analyse simulation data, and create visualizations to support research findings. Design and build prototypes
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond