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systems in the face of modern constraints such as optimization under uncertainty, constrained query evaluation, or the design of efficient, explainable, and scalable query engines. The successful applicant
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foundation. We are looking for a candidate excited by the challenge of rethinking data systems in the face of modern constraints such as optimization under uncertainty, constrained query evaluation
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. The group will be contributing to the Physics Modeling (MC software, MC validation and Pileup modeling), the MET High-Level Trigger validation, optimization and performance studies, and to the heterogeneous
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theoretical foundation. We are looking for a candidate excited by the challenge of rethinking data systems in the face of modern constraints such as optimization under uncertainty, constrained query evaluation
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. The group will be contributing to the Physics Modeling (MC software, MC validation and Pileup modeling), the MET High-Level Trigger validation, optimization and performance studies, and to the heterogeneous
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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structural topology optimization vision-based structural health monitoring autonomous and drone-based infrastructure inspection and vibration monitoring Successful candidates must hold a PhD degree in Civil
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associate will lead collaborative efforts in advancing research focusing on the intersection of infrastructure, climate, and human health. Examples of current active projects include: Developing optimization
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of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement learning, and Data-driven modeling and control. The Post-Doctoral associate will be based at NYU Abu Dhabi and will directly
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically