684 computer-engineer-"https:"-"https:"-"https:" positions at Nanyang Technological University
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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from the School of Physical and Mathematical Sciences with the School of Chemical and Biomedical Engineering. It is jointly run by the College of Science and the College of Engineering (https
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an emphasis on technology, data science and the humanities. The Data Science and Artificial Intelligence programme of LKCMedicine is a cross cutting programme that aims to bridge the gap between data science
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Fellow. The role will focus on helping to build thermal-flow engineering and
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for an experienced Chemical Process Engineer to join its
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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or Master's degree in Computer Science, Software Engineering, or a related field. Experience with Concrete-ML library from Zama or other FHE/crypto libraries. Hands-on Docker and CI/CD experience, comfort with
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purchasing, liaising, networking, field work. Job Requirements: Bachelor qualification degree in Engineering or computer science or related field At least 1 years of relevant experiences in data assimilation