313 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" Fellowship positions in Singapore
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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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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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international collaborators across clinical, academic, and industry settings to develop privacy-preserving machine learning approaches, federated learning frameworks, and interpretable algorithms for multimodal
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, Bioinformatics, Computational Biology, or other AI-related disciplines. Strong foundation in AI, statistical modeling, machine learning, or high-dimensional data analysis. Proficiency in programming languages
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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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sustainable technologies. For more details, please view: https://www.ntu.edu.sg/eee The LUMINOUS! Centre of Excellence for Semiconductor Lighting and Displays at NTU is seeking a Research Fellow (Quantum
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Research Fellow / Associate Research Fellow / Senior Analyst / Research Analyst (Military Studies Programme) The S. Rajaratnam School of International Studies (RSIS), a Graduate School of Nanyang
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function. Over the years, SBS has attracted talented individuals from around the world and Singapore to join as scientific leaders and researchers. For more details, please view https://www.ntu.edu.sg/sbs
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position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity
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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