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Field
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-FATES model using: Snow cover Flux tower data The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently
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About the Opportunity About the Opportunity: Northeastern University Pharmaceutical Industry Fellowships Program is a two-year experiential program designed to advance lifelong learning and the
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) Singapore. The incumbent has freedom to design the nature and type of deep learning simulations. Key Responsibilities: Utilize recently developed mathematical tools from algebraic topology, combinatorial
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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or Machine Learning). The Master’s thesis must be included in the application. Ideal Candidate: Demonstrates experience or strong interest in modelling, programming, systems thinking, and qualitative
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, Mathematics (Operations research) or Computer Science or Machine Learning). The Master’s thesis must be included in the application. Ideal Candidate: Demonstrates experience or strong interest in modelling
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learning with a focus on medical imaging, and programming with one or more of the major deep learning packages (PyTorch, TensorFlow, Caffe, etc.) is desired. Application Process Please upload the following
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one or more of the following areas: complex quantum processes, quantum error corrections, tensor networks, optimisation and machine learning, and developing software infrastructure Some experience in
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modeling, process design, process optimization, and machine learning in energy, environmental, and chemical processes. During his research career, Dr. Nguyen has authored more than 20 scientific papers, with
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processing, artificial intelligence, cognition and deep learning, machine learning, navigation and mapping, autonomous driving, assistive robotics, drones, dynamics and vibration, acoustics, medical imaging