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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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updates about Open Society’s work around the world By entering your email address and clicking “Submit,” you agree to receive updates from the Open Society Foundations about our work. To learn more about
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 7 hours ago
focus of your research will be on mining publicly available data repositories and use machine learning to discover linkages between heterogeneous biological, social, and environmental data and human
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learning. We are committed to fostering a supportive and nurturing environment. Through mentorship programs and wellness initiatives, we ensure the well-being and success of our community members. The PRODiG
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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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Department: Electrical, Computer and Biomedical Engineering Position supervisor: Dr. April Khademi Contract length: 1 year (with possibility of extension) Hours of work per week: 36.5 About Toronto
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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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your academic activities after completing your doctorate in order to perform military or alternative service, to care for close relatives, due to long-term illness, or, for example, to care for children