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Field
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Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply their expertise to advance predictive
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the Division of Engineering, New York University Abu Dhabi, is seeking a highly motivated Postdoctoral Associate to advance cutting-edge research in machine learning (ML). Our lab explores the intersection
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disciplines and involve expertise in optics, electronics, image and data processing using machine learning, photophysics, chemistry and biology. The position is therefore particularly well suited for candidates
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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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Python and GEE for geospatial analysis and data science. Experience with machine learning/deep learning frameworks (e.g., PyTorch, TensorFlow) applied to image or geospatial data. A track record of first
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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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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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nuclear physics detectors. Experience analyzing data from high energy or nuclear physics experiments. Familiarity with Monte Carlo simulations. Familiarity with machine learning techniques. About the
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solid experience in programming, particularly in Python and JavaScript. Significant experience in data science and machine learning will be highly valued. You like to work in a team while demonstrating