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the following tasks: Development of new large language models for process modeling Development of new decision-making algorithms Provide regular project updates to principal investigator and funding agency Report
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, Yong Loo Lin School of Medicine at the National University of Singapore (NUS) is seeking a motivated and experienced Research Fellow (RF) or Research Associate (RAssoc) to join our dynamic team in
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outputs across Projects 3-1 and 3-2 Manage and process large sets of operational data for case study analysis Contribute expertise in power grid optimisation to enhance planning models Participate in
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++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large
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for energy and catalyst, AI-assisted material design/screening, and the green flow processes/reactor design and understanding. For more details, please view https://www.ntu.edu.sg/mse/research. We are looking
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in signal representation/processing, esp for scent signals. Prior research experience and track record in signal detection, machine learning and deep learning. Prior programming experience in state
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data collection with stakeholders from participating schools, organize, and manage data storage (f) Process and conduct qualitative data analysis (i.e., transcribing, coding) (g) Write reports, be
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and materials processing methods for solid cooling devices. The candidate will play a crucial role in solid state chemistry synthesis, vacuum sealing, processing, characterization, property evaluation
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including key components such as cell configurations, flow channels, electrodes, membranes, and catalysts for HER and other electrochemical processes. • Conduct CFD and electrochemical simulations
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and development in the chemical conversion and valorization of hazardous waste streams, focusing on complex, reactive materials. Involves process design, optimization, and scale-up, including reaction