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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding
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molecular discovery. The position is ideal for a candidate who wants to turn deep mechanistic understanding into predictive models and closed-loop discovery workflows. Our lab develops and applies machine
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-source modeling and collaborative research. The successful applicant will play a central role in developing and applying Tools for Energy Model Optimization and Analysis (Temoa), a widely used open-source
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-source modeling and collaborative research. The successful applicant will play a central role in developing and applying Tools for Energy Model Optimization and Analysis (Temoa), a widely used open-source
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. The successful candidate will contribute to cutting-edge research in the modeling, design, fabrication, characterization, and system integration of MEMS quartz resonators for next-generation precision micro
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projects will be related to compound flood hazard and risk analyses as well as mitigation and adaptation strategies with applications through modeling and data analyses. Core Responsibilities: Collect and
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the nexus of AI, operations research and decision making and their applications to workforce policy and reskilling. The project builds on ongoing work using optimization-based models to predict future skill
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-informed decision making, and rapid advances in artificial intelligence and large language models, there is a growing need to investigate questions at the intersection of meta-research, open science, and
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Department of Carnegie Mellon University has an exciting opportunity for a technical postdoc for work on making large language models (and similar systems) safe and reliable, especially in contexts where
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machine learning. It focuses on developing innovative algorithms and models to address complex problems in diverse fields such as robotics, healthcare, and finance. The department offers a range of