792 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in Singapore
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Part-Time Lecturer for EE7207 Neural Networks and Deep Learning The School of Electrical and Electronic Engineering (EEE) at Nanyang Technological University, Singapore, invites qualified candidates
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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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Part-Time Lecturer in School of Electrical & Electronic Engineering - EE6203 Computer Control System
as Part-Time Lecturer for EE6203 Computer Control System. The Part-Time Lecturer is expected to teach this postgraduate course commencing in January 2026. This 13-week course will be offered
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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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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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visit https://ctlt.nus.edu.sg/ . More Information Location: Kent Ridge Campus Organization: Centre for Teaching, Learning and Technology Department : Teaching and Learning Employee Referral Eligible: Job
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the area of efficient and interpretable machine learning systems. The successful candidate will work on projects involving ensemble learning, large-scale data analytics, and high-performance model design
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of Electrical and Computer Engineering (ECE) at the National University of Singapore (NUS) is seeking a candidate at the rank of Assistant Professor (Tenure Track) in the area of machine learning and artificial
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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 Organization
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on Thurlings et al.’s models of feedback processes, most feedback in computer systems is cognitivist in nature. The advancements in LLMs appear promising in bridging this dialogic gap in feedback and learning