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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 11 days ago
Molecular Dynamics, virtual screening, free energy calculations and Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred. Create a Job Match for
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environment to grow and groom future business leaders. And we are looking to add to our BIZ family! To learn more about the NUS Business School, please visit https://bschool.nus.edu.sg/ Job Description We
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deep learning, on the topic “Analysis and Reconstruction of Digital Data Fragments”. This internship is intended for students at M2 level, or in the final year of an engineering school, interested in a
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machine learning and deep learning methods will be developed and applied within interdisciplinary research networks. The professorship should also contribute to the generation and supervision
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of experience in training, evaluating, and deploying machine learning models, including deep neural networks and relevant frameworks - Documented several years of experience in systems development with Python and
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Internal Number: 7072116 Learning Technologist For Accessibility Brown University To view the full job posting and apply for this position, go to: https://brown.wd5.myworkdayjobs.com/en-US/staff-careers
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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conferences (e.g., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding
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community-like atmosphere that fosters deep and impactful relationships with students and families from all walks of life over many years. P.K. Yonge is committed to creating a learning environment to support
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(HAC). This role focuses on applying advanced computational and analytical methods—including artificial intelligence, machine learning, deep learning, time-series modeling, and large language models