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Field
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the University’s research capacity in a globally relevant field. The role provides the opportunity to develop and publish a monograph based on Korean Studies-related PhD research or, if already published
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SUMOylation, transcription factors, or chromatin dynamics. Expertise in machine learning or statistical modeling for biological data. Knowledge of enhancer-promoter interactions and 3D genome organization. All
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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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University's Faculty of Arts and Sciences to study spatial and temporal aspects of interaction patterns in biological systems. We are looking for exceptional candidates with background in 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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Supervised Machine Learning and Reinforcement Learning. The objective is to significantly enhance battery performance and longevity. While conventional methods rely on either physics-based models or high-level
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data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python), including a sound understanding of FAIR data principles, data management and
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power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English English requirements for applicants from outside
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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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UKESM1 or similar models, advanced data analysis and machine learning, would be advantageous. Grade E: You will be near completion of a relevant PhD or have equivalent research experience, and be able