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Field
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The Research Fellow (RF) will conduct research in the field of coastal dynamics, with a focus on the development and application of machine-learning-enhanced coastal models. The project aims
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students from across the nation for future careers in the STEM workforce. All eligible candidates are encouraged to apply. Program Contact Want to learn more about the MLEF Program? Register for one of our
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applications for a PhD Research Fellow position in fairness in artificial intelligence, available at the Department of Informatics, in the Scientific Computing and Machine Learning (SCML) research group
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skills, including statistical analysis using R, Python, SPSS, Stata, or equivalent software. • Experience with computational social science methods, including NLP, machine learning, LLMs, social media
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computing environments and GPU computing. Proven experience in weather and climate models development and applications. Experience in machine learning, deep learning, or AI applications for atmospheric
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), machine learning algorithms, and perception methods can improve the autonomy, robustness, and precision of robotic manipulation in challenging environments. The project lies at the intersection of control
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sustainable manner. Key Responsibilities: Responsible for developing explainable machine learning algorithms for Tunnel Boring Machine (TBM) tunnelling and excavation Developing large language model enhanced
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collaborative and interdisciplinary activities. Job Requirements: Preferably PhD degree in Computer Engineering, Computer Science, Applied Mathematics or equivalent. Strong academic background in machine learning
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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scientific leaders and researchers. The group of Wang Zhongjian is looking for postdocs working on scientific computing and machine learning related topics. The funding is currently under a MOE grant entitled