18 agent-based-simulation "https:" Postdoctoral positions at Carnegie Mellon University
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critically on viable commercial mechanisms that support healthy development for model providers and downstream users. Core Responsibilities:Empty heading Analyze LLM-based commercial models by collecting
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intelligent autonomous systems operating under uncertainty, limited information, strategic human behavior, and complex multi-agent interactions. The postdoc will work at the intersection of control theory
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: Expert on steels and steel welding or additive manufacturing Develop advanced machine learning framework to combine different modality and fields of data Conduct CALPHAD-based simulations in a high
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different environments. Please check out the lab website for more descriptions of our research: https://sifangwei.github.io/ We are mainly looking for candidates who aim for an academic career. We will walk
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Department of Carnegie Mellon University has an exciting opportunity for a Postdoctoral Fellow. The SAT4Math project is developing solver technology that makes advanced SAT-based reasoning broadly accessible
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critically on viable commercial mechanisms that support healthy development for model providers and downstream users. Core Responsibilities: Analyze LLM-based commercial models by collecting, simulating, and
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-agent interactions in urban environments. Conduct research on how to comprehensively establish safety and risk assessment for autonomous vehicle systems by identifying potential failure modes, analyzing
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-agent interactions in urban environments Conduct research on how to comprehensively establish safety and risk assessment for autonomous vehicle systems by identifying potential failure modes, analyzing
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Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments. Modeling dynamical systems
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for the Pitkow Lab. Core Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments