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, Artificial Intelligence (AI) & Machine-Learning (ML) applications. Good written and oral communication skills Proficiency in power system modelling, advanced control theory (e.g., model-predictive control, etc
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research in formal verification, machine learning and artificial intelligence system assurance. The successful candidate will develop new techniques and tools for analysing, verifying and improving
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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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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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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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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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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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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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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
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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