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for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in
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Yield Forecasting". This project aims to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning
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written and verbal communication skills regarding research results. Preferred Qualifications: Experience with deep/graph neural networks and active involvement in data science and machine learning projects
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Responsibilities of the Post Conduct research and development on sign language recognition using computer vision and machine learning techniques. Lead the implementation of inference models suitable for mobile and
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, molecular dynamics, and machine learning, to model battery electrolyte and solid electrolyte interphase (SEI), while collaborating with experimentalists. Qualifications • Ph.D. in Computational Materials
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, Information Systems, or a related field with a strong research focus in machine learning, biometrics, or mobile computing. Proven experience in federated learning, privacy-preserving machine learning
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Number: 5269929 Distinguished Research Fellow- Khoury College of Computer Sciences About the Opportunity Khoury College of Computer Sciences is looking for a Distinguished Research Fellow. Responsibilities
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University of Western Sydney | The University Of Sydney, New South Wales | Australia | about 4 hours ago
of the University may be required. Please review the position description for further information. About You You hold a doctoral qualification in Cognitive Neuroscience, Machine Learning, Computer Science or another
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work that underpins the scientific research of the collaboration. Research Title: Process Modeling using Physically Informed Machine Learning The work will entail: § Designing and training physics
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded