1,436 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" positions in Singapore
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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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research impact. More information about the study can be found here: https://www.healthdata.org/research-analysis/gbd . Purpose of the post We seek a motivated, detail-oriented researcher enthusiastic about
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and groom future business leaders. And we are looking to add to our BIZ family! To learn more about the NUS Business School, please visit https://bschool.nus.edu.sg/ Job Description The Marketing Lead
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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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solutions. Through interdisciplinary programmes, living labs and large-scale testbeds, ERI@N drives impactful translational R&D with strong industry deployment. More details: https://www.ntu.edu.sg/erian We
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translate this understanding into disease alleviation and prevention. For more details, please view https://www.ntu.edu.sg/medicine/research/research-programmes/nutrition-metabolism-health We are seeking a
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a Research Fellow to work on the thermal catalysis and its
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records at the TRUST platform (https://trustplatform.sg/) . Large-scale proteomics data have also been generated for these individuals. We are inviting a motivated Research Fellow to join our PRECISE-SG100K
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and predictions. Use cutting-edge methodologies such as A.I. and machine-learning to accelerate the numerical simulation processes. Develop optimal control strategies for energy systems Publish high
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly