181 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" Fellowship research jobs at Nanyang Technological University
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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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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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participate in seminars, workshops, and public engagement activities Job Requirements: Doctor of Philosophy in Communication, Psychology, Sociology, Human-Computer Interaction, or a related social science
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. Key Responsibilities Plan, design, and implement independent research projects within a collaborative, multidisciplinary program Acquire and apply expertise in vitro reconstitution, live-cell imaging
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collaborative learning, you identify critical friction zones and promising ways forward, effectively accelerating the uptake of scientific innovations in real-world applications. Key Responsibilities: Collaborate
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Corporate Laboratory is seeking to hire a Research Fellow. The selected candidate will innovate research in advanced materials. Key Responsibilities: Work on AI-driven techniques such as machine learning and
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, such as, geometric/topological/algebraic data analysis, geometric/topological deep learning, Math for AI, categorical deep learning, sheaf neural networks, PINN/KAN models, neural operators, etc, and
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understanding of chronic wound pathogenesis. Key Responsibilities Plan, design, and implement independent research projects within a collaborative, multidisciplinary program Acquire and apply expertise in host
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expression systems Control of transcription, gene regulatory networks Synthetic biology, especially cell line engineering Immunotherapy, especially CAR-T/NK/M or dendritic cell therapies Diabetes, especially
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). Plan and draft cross-project analyses, synthesis sections, and learning summaries to disseminate CRCD research findings through publications and events (e.g., journal sections, pre-conference sessions