412 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs at Nanyang Technological University
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AI, Statistical machine learning, Large Language Models, Stochastic optimization, Transfer & Evolutionary optimization, Bayesian optimization or Complex Design Optimization. Key Responsibilities
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student Graduate Assistantship Programme (GAP) hours and seminar attendance. This role is integral to ensuring efficient academic administration and enriching students’ learning experiences throughout
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industry to enhance student learning, employability and programme relevance. The key responsibilities include (but not limited to): Overseas Immersion Programmes: Collate budget for each overseas course in
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). Operational knowledge of various mechanical testers & conventional machining is a plus point. We regret that only shortlisted candidates will be notified. Hiring Institution: NTU
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Management, and escalate unresolved at project team level. Requirements: Degree in Computer Science, Computer Engineering, or equivalent. Certified Project Manager, either CITPM or PMP certified, with at least
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research team as a Research Engineer. The successful candidate will support ongoing research initiatives by applying advanced machine learning, NLP, and large language models (LLMs) to develop next
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Centre) and auxiliary services (car parks and shuttle bus services) in NTU main campus and NTU@one-north. The Nanyang Executive Centre (NEC) is located at the NTU Main Campus. Currently undergoing
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will support functional process improvement and streamlining to meet university mission and vision. Candidate has an opportunity to learn more than 1 system in billing and collection, involved in system
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executive learning programmes for mid- to senior-level professionals across industries. Our programmes are delivered by world-class faculty and industry practitioners, supporting lifelong learning, leadership
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and analyze large-scale multi-omics datasets (genomics, transcriptomics, epigenomics) to derive biological insights Apply statistical and machine learning models to identify cancer risk biomarkers