174 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Fellowship positions at Nanyang Technological University in Singapore
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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Fellow to pursuing
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accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform performance, power, and area
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independently and as part of a team Experience with machine learning and AI applications in engineering is advantageous We regret to inform that only shortlisted candidates will be notified. Hiring Institution
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Research Fellow to develop high performance and
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a Research Fellow to work on the catalysis for CO2 related
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . Key Responsibilities: Develop and implement high-fidelity CFD and FEA simulation workflows for modelling heat
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a Research Fellow to oversee the progress of an oral drug
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, please view https://www.ntu.edu.sg/spms We are looking for a Research Fellow to complete the project on low dimensional quantum materials and devices and ensure the success of the project and support other
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of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop software prototypes for AI-for-Science systems tailored to scientific discovery and data