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Posting Details Posting Details Job Title Extension Agent for Agriculture and Natural Resources - Estill County Requisition Number RE51877 Working Title Department Name 81C01: KCES Region Central
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operationalizing next-generation LLM solutions that enable ING to streamline core processes, strengthen compliance, and scale agent-based AI systems. The position potentially targets at one of the following three
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planning tool which models how autonomous agents make decisions in an uncertain world. This project focuses on designing systems of interaction between agents in order to achieve complex, multi-objective
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the quality of uncertainty estimates by standard methods for LLMs, particularly with deep generative models, and (iii) develop a benchmark for uncertainty quantification in LLM-based scientific agents. The main
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University of California, San Francisco | San Francisco, California | United States | about 7 hours ago
offer components are subject to additional approvals based on UC policy. Your placement within the salary range is dependent on a number of factors including your work experience and internal equity
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Research Team ("DESRT") performs cutting-edge research and development on discrete-event simulations and their wide applications, especially, simulations of social phenomena using agent-based models, and
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of the following activities: Activity 1: Assessment of the direct effects of the biological control agent Trichilogaster acaciaelongifoliae Assess the establishment of the biological control agent along
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 23 days ago
cumbersome and costly, process-based (mechanistic) modeling has emerged as an effective alternative. However, many standard Process-Based crop Models (PBM) including STICS or DSSAT were initially built
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position within a Research Infrastructure? No Offer Description Want to explore how citizen collectives can drive societal change? Join us as a PhD in using AI-powered agent-based modeling to design adaptive
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at the interface of biological physics, agent-based simulations and machine learning to turn quantitative imaging data into a mechanistic, testable model of spindle positioning. In particular, we expect