785 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in Singapore
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Full Time Faculty, Tenure Track Position (Open-rank) in Learning Analytics - (2500004T) Description The College of Integrative Studies (CIS) at Singapore Management University (SMU) invites
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innovation. The Platforms Engineering Group builds and operates the infrastructure and systems that enable AI practitioners across AISG's programmes to develop, train, and deploy machine learning models
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Assistant at the National University of Singapore (NUS) Are you passionate about data science, machine learning, and artificial intelligence? Do you enjoy teaching and empowering others with valuable
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2022. We invite you to explore https://cde.nus.edu.sg/ece/ to learn more about us and see how you could become a part of our vibrant and diverse community. More Information Location: Kent Ridge Campus
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implementation of data-driven computer vision and machine learning models using sensor data, camera feedback, and process parameters for print and tool path planning and process optimisation. Deploy real-time
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in empirical analysis using econometric, machine-learning, and language-modeling techniques. Conducting literature reviews and synthesizing existing academic research to support ongoing projects
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adaptive decision systems. Contribute to research publications, technical reports, and open-source toolkits. Collaborate with faculty, postdoctoral researchers, and students on advanced machine learning
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including functional enrichment (GO, KEGG), network analysis, genome assembly and binning, systems biology, and multi-omics integration. Apply statistical modelling, machine learning, and deep learning
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related to generative design. The key responsibilities include the following: To independently undertake research in machine learning. To publish high-quality research papers as required by the funding body
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, machine learning, and deep learning models. Key Responsibilities: Develop and apply time-series forecasting methods for semiconductor equipment health monitoring. Analyze equipment degradation data