189 Computer-Science-"https:" "https:" "https:" "https:" "https:" positions at Nanyang Technological University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
duties assigned by the Principal Investigator. Job Requirements: Bachelor’s degree in computer science, artificial intelligence, data science, mathematics, software engineering, or a related discipline
-
Contributing to InVEST meetings and reports Job Requirements: Bachelor’s degree in Earth science, Geophysics, Geodesy or a closely related field Proficiency in computational methods, with experience in
-
CARTIN is a NRF medium sized center on advanced robotics. CARTIN aims to develop advanced robotics technology for applications in logistics, manufacturing and robots for humans. For more details
-
grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Dr Yingzhen Li (https://yingzhenli.net ) and her research group
-
schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . Our team is seeking a highly motivated Research Associate to contribute to cutting-edge research in embodied AI and
-
schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . Our team is seeking a highly motivated Research Assistant to contribute to cutting-edge research in embodied AI and
-
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
-
Globally recognized as a leading research and technology organization, the Nanyang Environment and Water Research Institute (NEWRI) addresses national priorities through its diverse expertise in
-
, Computer Science, Engineering, Biomedical Engineering, Health Informatics, Bioinformatics, Computational Biology, Applied Mathematics, Artificial Intelligence, Machine Learning, or a closely related quantitative
-
Science (e.g., Physics or Biology) or Engineering (e.g., Electrical, Computational). Practical experience with unsupervised and self-supervised learning workflows on datasets from scientific instrumentation