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platform to identify and optimize therapeutic candidates. Our group specializes in developing technologies to assess the multicellular environment within three-dimensional microtumor models. The project
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, Reinforcement learning, and Data-driven modeling and control. The Post-Doctoral associates will be based at NYU Abu Dhabi and will directly report to Prof. K.J.Kyriakopoulos, in close collaboration with other
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computational approaches to uncover mechanisms underlying complex diseases and to develop predictive, clinically actionable models. The successful candidate will work in a highly collaborative environment with
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driven two-dimensional materials and magnetic heterostructures. This position offers opportunities for collaborative theory development, advanced numerical modeling, and participation in a vibrant, multi
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characterization of germanium detectors, develop advanced Monte Carlo models and AI-driven analysis tools to optimize detector response, and to promote precision medical imaging and low energy dark matter searches
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of these systems are insufficient to cover the diversity of human-driven experimental activities. The development of multi-appendage, dexterous robots with embodied intelligence is a key to closing this gap
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for Vertebrate Genomics - providing exceptional opportunities for collaboration, mentorship, and intellectual exchange. Anticipated Division of Time 80% Research: Build, train, and evaluate cutting-edge AI models
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include: developing detailed analysis plans from preregistered protocols; conducting advanced quantitative analyses of longitudinal and dyadic data; handling missing data and conducting relevant sensitivity
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
developing the technologies that took on acid rain in the 1970s and mercury in the early 2000s. Program Goals The NETL Faculty Research Program (FRP) offers qualified academic faculty an opportunity
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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g