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, you will work on a cutting-edge, multidisciplinary research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural
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. The objective of this project is to elucidate the molecular mechanisms driving early DKD in individuals with Type 2 Diabetes in Barbados through deep molecular profiling and advanced machine learning tools. By
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 22 days ago
modeling (such as Molecular Dynamics, virtual screening, free energy calculations and Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 21 days ago
screening, free energy calculations and Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred. Special Physical/Mental Requirements Special
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 11 days ago
Dynamics, virtual screening, free energy calculations and Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred. Special Physical/Mental
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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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. DESIRED QUALIFICATIONS: BS, MS, MBA, or PhD in Business, Science, or a related field. Minimum of seven years of relevant experience in the healthcare technology industry, including startups, corporates
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https://engineering.purdue.edu/PMRI). The population of officers at Purdue currently exceeds 100 students pursuing PhDs and MS degrees. We intent to grow this number to build a population of unique
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., turbine components).Research on advanced deep learning techniques, including architectures based on GRU, LSTM, attention mechanisms, and hybrid models.Implementation of real-time predictive models (soft
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. They will learn to design interpretable, legally robust AI systems, including attention-based deep learning models and reinforcement learning approaches that adapt lineup presentation in real time based