240 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" research jobs at Nanyang Technological University in Singapore
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. Learn more about our lab at https://www.richardshelab.com/ . Key Responsibilities: Design and lead a novel research project aligned with your scientific interests and the lab’s experimental strengths
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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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translate this understanding into disease alleviation and prevention. For more details, please view https://www.ntu.edu.sg/medicine/research/research-programmes/nutrition-metabolism-health We are looking
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in Communication, Human-Computer Interaction, Information Science, Psychology, or a related field. At least 1 year of relevant experiences in doing research in a relevant field. Familiarity with social
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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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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 thermal catalysis for CO2
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A Postdoctoral Fellow position is available in Prof. Tong Ling’s Lab (https://www.tonglinglab.com ) at Nanyang Technological University, Singapore. The successful candidate will work with our
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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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encouraged to apply. This position focuses on research assessment delivery and study coordination For more details, please view : https://www.ntu.edu.sg/medicine/drcs and https://www.drcs.sg/ Key
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superlattices (twistronics). The role will focus on developing and applying theoretical models and computational quantum chemistry and machine learning methods to uncover novel properties and phenomena in low