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within a Research Infrastructure? No Offer Description The Role The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial
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applications for algorithms and methodologies based on state-of-the-art research in machine learning and big data for collaborative machine learning. Responsibilities Design and write robust, readable, and
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Description The candidate will research methods combining classical and quantum machine learning on graphs datasets, with applications to drug development. Job Requirements The candidate should hold a Ph.D. in
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to making groundbreaking discoveries in cancer genomics using cutting-edge machine learning techniques. Our research focuses on the causes and consequences of genome instability. We explore this by combining
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change and epidemiology, machine learning and global health. This work will allow you to collaborate with a broad range of people at the School of Public Health as well as public health professionals and
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at the Department of Electrical and Computer Engineering, National University of Singapore (NUS). This project will combine the strengths of machine learning and control theory and consider the complex dependencies
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good research record in battery areas is required Similar research background and good writing skills are required. The candidate should be either an optimization expert or a machine learning expert
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learning expert. Deep understanding of optimization, machine learning, and artificial intelligence is highly desired Strong motivation and interest in staying in academia are desired A good publication
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Associate/Assistant in Infectious Disease Modelling and Machine Learning for Public Health Location: Singapore Salary: Commensurate with experience The National University of Singapore's Saw Swee School
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the National University of Singapore (NUS). Job Requirements At least a bachelor degree in civil engineering, hydrology, water resources engineering, optimization, seasonal forecasting, machine learning, or from