524 algorithm-"Multiple"-"Prof"-"U.S"-"Simons-Foundation" "University of Wisconsin Madison" Fellowship positions
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on complex system subject to various constraints. Design and develop real-time algorithms. Simulate and evaluate system performance. Document research outcome to publish at international conference / journal
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advances the mathematical foundations, algorithms, and real-world applications of epistemic uncertainty in machine learning, with a strong focus on imprecise probabilities, uncertainty representation and
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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particular sequential, multiple assignment, and randomized trial design. You will have the opportunity to mentor the PhD students on the team. Experience in any of the following areas may be useful: SMART
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dialogue on AI governance. Manage multiple projects simultaneously, ensuring timelines are met and resources are effectively allocated. Collaboration & Knowledge Exchange Collaborate with policymakers
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state-of-the-art facilities to work on the following: Developing advanced path planning, search, and exploration algorithms for multi-UAVs systems in unknown and complex 3D environments. Designing
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modelling, and the economics of mental health Support economic analysis of healthcare utilisation, outcomes and costs using national datasets Develop and apply algorithms for cost-effectiveness analysis
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) at Harbor Branch Oceanographic Institute/Florida Atlantic University. Currently, SAIL is conducting multiple projects ranging from Hybrid Aerial Underwater Robotic System (HAUCS) – a cyber physical system
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems