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Position Description Postdoctoral Associate – National Tutoring Observatory Cornell University Description The National Tutoring Observatory (NTO) is based in Cornell’s Ann S. Bowers College
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autonomous systems that collaborate effectively while controlling what outside observers can infer? In this PhD project, you will develop security-aware planning and control methods for multi-agent cyber
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, curriculum, and lifelong learning Agentic foundation models, tool use, self-improving or self-updating AI models Representation learning, cross-modal alignment, and multimodal learning Your profile Excellent
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general medical and surgical conditions based on knowledge of the indications, contraindications, side effects, interactions and adverse reactions of pharmacologic agents and other relevant treatment
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 13 hours ago
, developing processes and procedures for monitoring, alerting, detection, and response functions for on-premise, cloud-based, and, as appropriate, third-party systems and services. Review system logs and real
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modeling. The SCI Institute presents a highly challenging, collaborative work environment that can be deeply rewarding for the right individual. Further information is available at http://www.sci.utah.edu
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approaches such as protein diffusion models, flow-based models and related methods. Your work will contribute to ProteinCAD, a computational design framework for creating protein structures with specified
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Infrastructure? No Offer Description Use real-world vessel data, agent-based modelling and digital twin technology to accelerate the transition toward zero-emission inland shipping. Job description The
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benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time-limited positions may be eligible for all, some, or no benefits, based on the grant
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Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis