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Complex Data Analysis ○ Areas of Research: Algebraic methods in data analysis, optimization, topological data analysis, geometric deep learning. ○ Considered a plus: experience in programming or course
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deep learning, computer vision, or generative AI. Demonstrated experience with one or more deep learning frameworks (e.g., PyTorch, TensorFlow). Demonstrated ability to work with large-scale Earth
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Computational Quantum Chemistry Scientific Computing Machine Learning/Deep Learning Structural Bioinformatics High Performance Computing Complex mathematical modeling and simulations Leadership
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for the Itararé and Rio Bonito Groups; develop predictive prospectivity models using machine learning, deep learning, and AI; apply spatial interpolation to develop favorability maps; integrate
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background, and an outstanding MSc degree in Engineering, Computer Science, Physics, Applied Mathematics, or a related field. You should be proficient in or willing to learn generative deep learning – in
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programming skills in Python, and experience with at least one deep-learning framework (PyTorch preferred).• A solid grounding in machine learning. Experience with representation learning, generative
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
quantitative background and a track record of first-author publications in peer-reviewed journals -Experience designing, training, and evaluating deep learning models in Python (PyTorch preferred
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mobile apps.", USENIX Security, 2021. Required knowledge Knowledge in privacy-enhancing techniques; Knowledge in machine learning and deep learning; GPA: H1E with minor thesis (HD) Project funding
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mobile apps.", USENIX Security, 2021. Required knowledge Knowledge in privacy-enhancing techniques; Knowledge in machine learning and deep learning; GPA: H1E with minor thesis (HD) Project funding
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knowledge of methodologies such as deep and statistical learning. Excellent communication skills, including the ability to write for publication, present research proposals and results, and present the