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Field
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About the Opportunity The successful candidate will contribute to an ambitious project developing perceptual AI agents that assist humans in daily activities through behavioral understanding and
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emulators, or agent-based modeling. Knowledge of scenario development, resilience frameworks, and socio-environmental-technological systems. Experience with visualization tools (e.g., dashboards, GIS, spatio
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virulence and host resistance, as well as characterizing microbial biocontrol agents. The successful candidate will employ resistance screening of hosts, transcriptomic and genomic profiling to compare
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Postdoctoral Associate – National Tutoring Observatory Postdoctoral Associate – National Tutoring Observatory Description The National Tutoring Observatory (NTO) is based in Cornell’s Ann S. Bowers
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multi-agent pathfinding (MAPF) algorithms - Experience across multiple areas is a strong plus; Experience developing ML-based optimization approaches is a strong plus; A strong publication track record is
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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of the energy sector, aligned with the principles of Industry 4.0 and the RAMI4.0 reference model, through a collaborative and interoperable solution based on Multi-agent Systems and Asset Administration Shells
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modeling software. Proficiency in chromatographic and FTIR analytical techniques. Skilled in analytical methods for catalytic/separation agents materials characterization. Solid understanding of chemical
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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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: Apply Position Description Postdoctoral Associate – National Tutoring Observatory Cornell University Description The National Tutoring Observatory (NTO) is based in Cornell’s Ann S. Bowers College