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Field
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. Applicants with a strong background in optimization (including machine learning), algorithmic game theory, decision theory, computational social choice, social welfare, or fairness optimization are welcome
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with data visualization (graphs, GIS maps, figures). Proficiency with GIS software and spatial data analysis is highly desirable. Strong writing skills, including the ability to contribute to manuscripts
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in writing scientific papers based on research findings. This includes generating graphs, tables, and other visuals for internal reports, grant applications, and publications. Collaborates with other
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applications to this selection procedure, provided they hold a doctoral degree* in Mathematical Logic, Set Theory or similar areas, and fully comply with the following requirements: Demonstrated scientific and
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significant experience in both theory and experiment. Please submit a curriculum vita and a list of publications. For full consideration, applications should be received by November 20, 2025. Interested
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role in the analysis of human linguistic communication, e.g., underpinning theories of pragmatic language use. This project is contributing to an active and growing research program investigating how
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of Computer Science and Technology at the University of Cambridge, UK. This position is part of a broader effort to advance fundamental research in classical and quantum complexity theory. The successful candidate will
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Theory Artificial Intelligence and its Mathematical Foundations Mathematical and Statistical Methods for Big Data Analytics Mechanism and Data Modeling with Integrated Applications Requirements: Under
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Systems (MAS) theory: cooperation, negotiation, coordination, and competition. - Game theory and reinforcement learning for distributed optimization for agents' properties (e.g., perception, reasoning
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interest in expanding their knowledge in both domains. (1) Geometry/Topology -related methods in computer science. (2) Machine Learning. (For example, graph neural networks, generative networks, or neural