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Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for communication networks. Key Responsibilities: Develop signal processing and machine learning
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Job Description Job Alerts Link Apply now Job Title: Research Analyst/ Associate/ Fellow in Machine Learning and Artificial Intelligence (ML/AI) Posting Start Date: 19/09/2024 Job Description: The
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . The School of Mechanical and Aerospace Engineering (MAE) is seeking to hire a Research Fellow, Applied Machine
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topics ranging across programming language (especially Bayesian statistical probabilistic programming), statistical machine learning, generative AI, and AI Safety. Key Responsibilities: Manage own academic
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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requirements: PhD Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, obtained within the last five year Research Experience in one or more of the following
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project