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, working closely with the Core Outcome Measures in Effectiveness Trials (COMET) Initiative. You will develop and evaluate natural language processing and machine-learning methods (including large language
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. Knowledge of survival analysis. Knowledge of machine learning methods. Other Requirements Application materials must include: Curriculum Vitae (CV) Statement of research interests Names of three professional
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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following areas is desirable: collection and analysis of dense nodal seismic datasets, ambient noise tomography, high-performance computing, machine learning applications in observational seismology, and
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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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geoscientific process models, as demonstrated by presentations, publications and/or repositories Expertise in applying Bayesian statistical methods, machine learning methods, or related statistical inference
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machine learning tools, to study how genes are switched on and off and how they interact — and fit these models to single-cell data to test how well they explain what's actually observed. ● Co-author
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. The postdoctoral researcher(s) will join an international research environment at Umeå University, including Stat4Reg (www.stat4reg.se ), which develops statistical and machine-learning methods for register data
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 12 days ago
-series. Experience exploring machine learning and deep learning techniques for geospatial applications is highly desirable to effectively engage with Earth observation foundation models. Technical
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analysis. Excellent programming skills in Python and experience with deep-learning frameworks (preferably PyTorch). Experience developing, training, validating, and optimising machine-learning models