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will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning
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Epidemiology of Malaria), led by Aimee Taylor. Using simulation-based inference (SBI) with deep learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum
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committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing varying opinions and perspectives strengthens our
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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analysis, and data visualization. Apply advanced statistical, machine learning and AI methods when appropriate. Review analysis outputs and ensure methodological consistency and quality. Collaborate with
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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initiation latency, movement speed, gait characteristics, postural control, motor variability, and other behavioural descriptors. ESSENTIAL REQUIREMENT PhD in machine learning, artificial intelligence
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University of California, Los Angeles | Los Angeles, California | United States | about 21 hours ago
seeking applicants for a full-time postdoctoral scholar position in Computational Immunology and Genomics. The successful candidate will develop and apply computational, statistical, and machine-learning
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a sequential decision-making process explored through computational simulation and deep multi-objective reinforcement learning. The project will investigate a simulation platform that reproduces