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Field
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deployment. Experience with reinforcement learning (RL), computer vision, and sim-to-real transfer. Experience with robotic hardware platforms such as mobile robots, robotic arms, and embedded sensors
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have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding of neuroimaging data to predict subjective
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Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization
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on reliability, security, and resilience of electric power systems and microgrids and stability analysis and Scientific Machine Learning (SciML) for microgrid applications. The successful candidate will be
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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) and spatial Machine Learning (ML) models Salary and full employee benefits are offered in accordance with Princeton University guidelines. The Term of appointment is based on rank. Positions
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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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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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have experience in computational neuroscience and data mining using machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal neuronal