417 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" uni jobs at Nanyang Technological University in Singapore
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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
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/3D animation studios. This role is central to enabling high-quality, future-ready teaching, learning, and research across animation and adjacent disciplines such as Interactive Media, Game Design, and
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computational analyses (e.g., regression, network analysis, machine learning). Academic writing skills and willingness to co-author publications. Strong problem-solving skills and ability to work independently
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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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Manage day-to-day operations of the cohort management, including interactions with programme partners, instructors, venture builders, founders, and mentors. Coordinate learning modules, expert sessions
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tools (e.g. RPA, intelligent document processing, workflow automation) Experience designing dashboards and reports using modern BI tools (e.g. Power BI) Working knowledge of AI / machine learning concepts
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digital humanities, ludic studies, or social gaming platforms. A passion for education and the ability to foster a supportive, inclusive, and diverse learning environment, with strong interpersonal and
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to machine learning, process design, mass balance, cost analysis, and life-cycle-analysis preferred Industrial experience in scaling-up design and productization preferred Good team-player, good communication
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applications for a Visiting Professor position in Computational Statistics, Statistical Signal Processing, Bayesian Inference, or Machine Learning. Candidates should hold a Ph.D. in statistics, mathematics
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digital integrated circuits, utilizing deep learning techniques for better adaptability and productivity. The PACE team aims to advance side-channel and fault analysis techniques for hardware security