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to apply advanced AI models in areas such as catalyst design, multi-scale modeling, and spectroscopic analysis. The Research Fellow will take on a significant role in machine learning theoretical energy
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team to conduct the research on development of AI models and algorithms for image processing, computational imaging as well as computer vision applications. The roles of this position include: Research
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team to conduct the research on development of AI models and algorithms for image processing, computational imaging as well as computer vision applications. The roles of this position include: Research
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the system Development of inverse design frameworks using machine learning Development of full simulation for the chip-scale chirped-pulse amplification Use the full simulation to guide system fabrication
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. Perform any other duties relevant to the research programme. Job Requirements: PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive
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by using explainable AI To develop generative AI techniques to design novel biologics for cancer Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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science, machine learning, artificial intelligence, or a related field. Candidates with a PhD may be considered for a Research Fellow position instead. Prior experience with video data visualization research will be
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, Safety and Health Regulations. • Assist in project resource requirements and managing student projects. Job Requirements: • Have a PhD Degree in Computer Engineering/Computer Science/Electrical Engineering
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: Python, R, Java, C++, C#.Net, SQL. Proficiency in using Business Intelligence tools (e.g. Power BI, Tableau or Qlik Sense) Experience in applying machine learning techniques and designing algorithms
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, leveraging advanced learning analytics, machine learning, and deep learning techniques. The candidate shall work under the supervision of the Principal Investigator (PI) and Co-PIs to conduct academic research