50 machine-learning "https:" "https:" "https:" "https:" "https:" Fellowship research jobs in Singapore
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian Multi-Energy System & Grids Team is looking for a Research Fellow in
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within a Research Infrastructure? No Offer Description Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the
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third largest university by intake in Singapore. SIT’s mission is to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society
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/knowledge graphs, and carbon accounting. The Research Fellow will help develop and lead the CognitionX Lab (https://cognitionx-lab.github.io/ ) with Dr. Jinying Xu, Assistant Professor and Director of
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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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, machine learning, and life cycle assessment, we aim to create sustainable wearable systems to enhance human well-being. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking
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experimental data from both literature and in-house experiment results Use state-of-the-art machine learning models to develop a multi-scale droplets evaporation model Assists in co-supervision of Final Year
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superlattices (twistronics). The role will focus on developing and applying theoretical models and computational quantum chemistry and machine learning methods to uncover novel properties and phenomena in low