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for Computer Animation, The Media School and the School of Psychology. The breadth of subject areas in the Faculty means our cutting-edge research is delivering real benefits to digital creative industries
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time associated with family planning, military service, illness, or other life-changing events. This position is based at Upton, NY, but may involve a temporary assignment of approximately 3–6 months
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on behalf of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL
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in international research visits if needed. We are looking for a highly motivated researcher with: A PhD in machine learning, computer vision, remote sensing, glaciology, climate science, or a related
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combinations of theoretical physics, mathematics, and machine learning. While machine experience is not a strict requirement for the job, we anticipate that the strongest candidates will have clear research
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industrial conditions. Keywords: Artificial intelligence, autonomy, digital twin, edge computing, UAV systems. Objectives: Support the development of AI and machine learning algorithms for autonomous
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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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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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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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» AlgorithmsYears of Research ExperienceNone Additional Information Eligibility criteria - PhD in one of the following areas (or related fields): * Machine learning / deep learning * Quantum computing / quantum