519 algorithm-"Multiple"-"U"-"Prof"-"Simons-Foundation" "University of Wisconsin Madison" Fellowship positions
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for Multi-Agent Decision-Making, https://oceanerc.com ). This timely project will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making
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Centre for Advanced Robotics Technology Innovation (CARTIN) is looking for a candidate to join them as a Research Fellow. Key Responsibilities: Develop novel algorithms for multi-agent inverse
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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. The successful candidate will play a pivotal role in a project centered around variational quantum algorithm in the near-term, especially on innovating advanced error mitigation or detection techniques to solve
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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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The Society offers postdoctoral fellowship grants to unusually promising recipients of M.D., Ph.D. or equivalent degrees when it appears that the program of training to be supported by the grant will enhance the likelihood that the trainee will perform meaningful and independent research...
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) Design robust obstacle avoidance algorithms for mobile robots in dynamically changing environments, focusing on formal safety constraints and real-time performance in unpredictable conditions. b) Develop
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Finding a way to stop MS, restore function and end MS forever will require a cadre of well-trained scientists engaged in MS-related research. The Society’s Career Transition Fellowship addresses this need by fostering the development and productivity of young scientists who have potential to...
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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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