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advances the mathematical foundations, algorithms, and real-world applications of epistemic uncertainty in machine learning, with a strong focus on imprecise probabilities, uncertainty representation and
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industry partners. Job Requirements: PhD degree in Computer Science/Engineering, Electrical/Electronic Engineering, Mathematics or other related disciplines from a reputable university. Good publication
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, NeurIPS, ICML, ICLR, and etc. Experience in interdisciplinary studies of deep learning, mathematics, and physics is preferred. Strong theoretical background in quantum learning theory, quantum many-body
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Join Our Team at the School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore The School of Physical and Mathematical Sciences (SPMS) at NTU Singapore hosts research
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evaporation process Job Requirements: Bachelor in Materials Science and Engineering, Energy system, Applied Mathematics, or related field. Experience in Perovskite materials and solar cells Expert in Perovskite
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journals such as S&P, USENIX, SIGMOD, VLDB, TODS, NeurIPS, ICML, AAAI, or ICLR. Job Requirements: Preferably bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related
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Join Our Team at the School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore The School of Physical and Mathematical Sciences (SPMS) at NTU Singapore hosts research
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Engineering, Computer Science, Applied Mathematics or equivalent. Strong background in machine learning, convex optimization, or distributed systems. Prior experience in federated learning, edge computing
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for analysis. Support data analysis, including descriptive statistics, generation of graphs, tables, maps and other innovative figures to visualize health data. Contribute to key publications, including
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Join Our Team at the School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore The School of Physical and Mathematical Sciences (SPMS) at NTU Singapore hosts research