158 computer-science Fellowship positions at Nanyang Technological University in Singapore
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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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research profile and prepare for the next career stage. Job Requirements: A PhD degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, Applied Maths, Physics, or any related
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to the project. Job Requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. Min 3 years of relevant experience in computer vision, artificial intelligence, etc
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PDEs arising from emerging applications. The hire is in line with a university wide initiative to advance the application of Computational Science in interdisciplinary research. Key Responsibilities
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necessary lead relevant meetings. To undertake any other duties relevant to the programme of research. Job Requirements: PhD degree in Computer Engineering, Computer Science, Electronics Engineering or
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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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applies AI to tackle challenges in aquaculture and drug delivery, interface of materials science, biology, and computational modeling. Key Responsibilities: Lead and execute AI-driven research projects in
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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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Electrical and Electronic Engineering, Applied Mathematics, or fields related to Computational Science and Engineering More than 5 years of research experience in the related area Experience in code
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epidemiology, bioinformatics, computational biology). Candidates who have successfully defended their thesis or dissertation are welcome, subject to evaluation on a case-by-case basis. Experience analyzing large