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Field
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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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of design, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and
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Physics , Higgs physics , LHC , Machine Learning , Neutrino , Particle Theory , Phenomenology , Quantum chromodynamics , Quantum Field Theory , Theoretical Particle Physics Appl Deadline: 2025/12/08 11:59PM
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a team-oriented research environment. PREFERRED QUALIFICATIONS Prior experience in one or more of the following areas: longitudinal data analysis, survival analysis, spatial methods, machine learning
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discovery machine for unlocking the secrets of the "glue" that binds the building blocks of visible matter in the universe. The machine design is based on the existing and highly optimized RHIC Ion-Ion
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational
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are required, as well as experience with machine learning, and some familiarity with the major bioinformatics tools/databases. Experience with high performance computing and protein function and/or structure
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for candidates with a Ph.D. in economics, management, political economy, or related areas with expertise either in game theory, particularly mechanism design or experimental methods and machine learning. The term
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or, preferably, scientific machine learning (SciML). • Conducting research related to the improvement of the hygrothermal properties of cross-laminated timber. Desing and perform testing and analysis crate