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Requirements: Preferably PhD in computer science or related field. Expertise in computer programming Knowledge in machine learning Proven research ability as evidenced through a portfolio of publications and/or
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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Investigator (PI) or team lead with project management tasks. Job Requirements: PhD degree in Optimization, Artificial Intelligence, Transportation or Aerospace. Evidence of developing Machine Learning and
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diffusion models using path integral formulations. This project aims to advance quantum machine learning by: Designing a quantum counterpart of diffusion models; Leveraging path integral methods to model
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. The role will focus on developing machine learning and mathematical optimization solutions for electric vehicle fleet charging optimization under different constraints. Key Responsibilities: Formulate
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(CBmE) was established in September 2006 in the Yong Loo Lin School of Medicine through a generous gift by the Chen Su Lan Trust. CBmE, directed by Prof Julian Savulescu, is a thriving centre for learning
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: PhD in Materials Science, Chemistry, Physics, Computer Science, or a related field. Strong expertise in machine learning for materials science (e.g., generative models, neural networks, active learning
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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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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