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, Computational Linguistics, Machine learning, Computer Engineering or related fields Preferred Qualifications: ● Strong experience implementing and training deep learning models in PyTorch, with attention
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of faculty at SUNY Polytechnic Institute and the University of South Florida, consisting of mathematicians, physicists, computer scientists, and engineers investigating applications of deep learning
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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numerical research. Your primary research project will focus on Naturally-occurring Deep Eutectic Systems (NADES) and their low temperature behavior, but you will have some latitude to study a variety of
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numerical research. Your primary research project will focus on Naturally-occurring Deep Eutectic Systems (NADES) and their low temperature behavior, but you will have some latitude to study a variety of
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional
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shocks from the past and places them into a future scenario. What can we learn from the past to improve future climate projections and preparedness? It will drastically expand the available evidence by
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learning. The successful candidate will be expected to engage in all of these activities. In collaboration with the science education research groups at the faculty, the candidate will gather and analyse
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laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications relevant to environmental data analysis. Basic knowledge of GIS/mapping tools