355 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Nanyang Technological University
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Responsibilities: Conduct individual research within the designed project: process data, develop research methods, build and evaluate computer vision and machine learning algorithms empirically. Author research
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equivalent. Strong background in machine learning and computer vision. Prior experience in data-efficient classification, synthesis, and detection is preferable. Strong publication records in top-tier machine
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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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and intelligent networked systems, including theoretical and system-level research Demonstrated capability in advanced communication technologies, antenna systems, and machine learning–enabled methods
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Requirements: Preferably Master's degree in Computer Science or related field. Prior experience in NLP or relevant areas is a plus. Good programming skills (Python), experience with machine learning and LLM
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background/interest in time-series analysis, theoretical machine learning on networks, and high-dimensional statistics. Key Responsibilities: Take the lead in developing sub-projects (problem formulation
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Singapore, Indonesia, and the broader Southeast Asian region. Experience with machine learning or data-driven approaches for subsurface imaging or hazard assessment (preferred). We regret to inform that only
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quantum information theorists to integrate secure key rate calculations with simulations. Investigate and apply AI and machine learning techniques to improve and support secure-by-design development
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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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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