705 parallel-and-distributed-computing-"Meta"-"Meta" positions at Nanyang Technological University in Singapore
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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. Write the report for the project progress. Work with research assistant for the prototype. Job Requirements: PhD in Electrical and Electronic Engineering, Computer Engineering / Science, or related field
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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status and family responsibilities, or disability. Job Description: We are seeking part time lecturers to teach one or more courses in the MSc in Modelling and Simulation program. The program and
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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As part of the Learning & Talent Management team, the candidate will be responsible for the formulation and end-to-end implementation of the Management Associate Programme (MAP). The key
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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. Requirements: Bachelor’s Degree in Computer Science, Computer Engineering, Software Engineering or related discipline. At least 20 years of IT experience which consist of: 10 years of project management
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model is employed to forecast renewable energy availability, providing crucial insights for the design optimization process. The ML-assisted operation tackles the dynamic optimization of parallel energy
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems