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support the development of AI-driven and data-driven approaches for the discovery and design of functional materials. The role will involve the development and application of machine learning models, high
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on a project in the area of power system risk modeling and assessment. Key Responsibilities: Develop a probabilistic security assessment framework for heterogeneous operational uncertainties and
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demonstrate expertise in seismic data processing and modelling, dense array analysis, distributed acoustic sensing, and seismoacoustics, and a strong track record of publishing impactful research in areas
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of the external grids Establish a stochastic differential algebraic equation (SDAE) based analytic framework for interdependent electromechanical and electromagnetic dynamics modelling and analysis Design data
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. The research will broadly be in the area of stochastic growth models and the Kardar-Parisi-Zhang universality class, though related areas of probability may also be of interest. The position is for a maximum of
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at NTU are looking for a Research Fellow (RF) to carry out research in probabilistic machine learning and GenAI, by exploring cutting-edge approaches such as sequence model design, continual learning
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intelligence, including machine learning and computer vision, robotics, and physics-based modelling, the DISC Lab pioneers new methods for monitoring, digitalization, and automation in construction. We
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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data analysis, particularly structural equation modelling, using MPLUS/AMOS/R With evidence of proficiency in academic writing, such as published journal papers focusing on social network analysis
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, or a related field Strong background in computational modelling of surface chemistry and oxide materials Experience in developing and training interatomic machine learning potentials Experience in