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Field
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, Computer Science, Electronics Engineering or equivalent. Experience in one or more of the following areas: machine learning, deep learning, software-hardware co-design, computer system performance, design
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that aims to be a world leader in environmental research focused on Asian environmental challenges. The ASE integrates earth and environmental life science, ecology, engineering and technology, human ecology
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from the Department of Civil and Environmental Engineering. This position is part of an exciting research programme aimed at advancing the multi-robotic wire-arc directed energy deposition technology and
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School of Electrical and Electronic Engineering is one of the founding Schools of the Nanyang Technological University. Built on a culture of excellence, the School is renowned for its high academic
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, Geography, Civil Engineering, Computer Science, Mathematics, Physics or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning
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metallic components (ferrous and non ferrous). Job Requirements: PhD (or Engineer with minimum 2 years of experience) in materials/mechanical engineering, in the field of solid state material recycling
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June 2026 (although funding is in place for a six-month extension). The successful candidate will join a multidisciplinary team in Mechanical Engineering and Civil and Environmental Engineering, and will
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multidisciplinary team in Mechanical Engineering and Civil and Environmental Engineering, and will have the following responsibilities: Development and implementation of hardware and software; Data analysis and
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science, computational biology, engineering, statistics, mathematics.). Experience and interest in prediction modelling Proficient in statistical software and programming languages and familiarity with relevant libraries
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Environmental Engineering, and will have the following responsibilities: Development and implementation of hardware and software; Data analysis and modelling; Coordination of field measurement and data analysis