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applications. Research activities may involve geophysical forward modeling, AI-driven geophysical inversion, seismic monitoring and imaging, scientific machine learning, depending on the specific research focus
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to predict marine extremes for engineering and navigation purposes The PhD candidate is expected to develop an integrated framework that combines machine and deep learning methods with statistical and
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experience in AI security, data privacy or machine learning. High-quality publications in top-tier software engineering/security/AI journals or conferences. Proficiency in programming software/languages
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processing algorithms Development and implementation of novel pulse sequences Acquisition of high quality NMR data Interaction with other research groups, learning new techniques where necessary Close
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degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image
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comparison with predictions from machine learning models • Close collaboration with researchers in charge of machine learning, algorithmic architecture and performance analysis • Contribution to the scientific
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to research projects involving big data analytics, artificial intelligence, and machine learning applied to stroke care. Support the development and validation of predictive models and clinical decision-support
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machine learning-based model to map satellite retrievals to ground based air pollutant concentrations Conducting error assessment on the derived concentration data Implementing new observational data
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physics. Candidates for the position must have a PhD in physics or a related discipline, preferably with expertise in stochastic processes, nonlinear dynamics, and biological physics. The intended start
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for postdocs. UNLV currently employs postdoctoral scholars across a wide range of disciplines. Learn more about UNLV's postdoctoral scholars. MINIMUM QUALIFICATIONS This position requires a PhD in Chemistry