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Field
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy
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problem-solving skills, with a focus on developing innovative solutions for multi-modal LLMs. Self-motivated and able to work independently, managing multiple tasks and projects in a fast-paced environment
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Innovation (UKRI), focusing on populations with multiple long-term conditions. You will contribute to a social care initiative, developing and testing an AI-informed digital tool to help individuals with
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designs and methods, clinical trial methods, Bayesian methods, and developing R packages and scalable algorithms. Opportunities for collaboration across the Department of Biostatistics and the Medical
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inferences, but are also developed in a manner that garners public confidence in their applications. To achieve this confidence, we need to prove that the conclusions drawn from machine learning algorithms
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research initiatives that analyze the impact of AI technologies on social systems and design innovative methods for adapting economic and social governance to AI development. A special focus will be
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project bridges two foundational fields in computer science and mathematics: Theory of Algorithms and Extremal Combinatorics. By integrating these areas, the project seeks to develop innovative
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(CPS) for aquaculture, to sensors and platforms for maritime applications. The Postdoc’s primary task will be to lead the development of algorithm, software, and hardware to extend the current HAUCS
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creative ideas in supportive environments. The clinical infrastructures include multiple imaging scanners, including a long axial field-of-view (LAFOV) PET/CT scanner, and aims to push the limits of modern
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Baltimore, MD, or Washington, DC , to investigate the foundations of human normativity and how these insights can inform the development of AI systems aligned with human values. The ideal candidate will have