82 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"SciLifeLab" Fellowship positions at Nanyang Technological University
Sort by
Refine Your Search
-
Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
-
Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
-
Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
-
schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research fellow to work on the development of data-enabled predictive controller on autonomous
-
on musculoskeletal health in occupational and community settings. Design and implement cohort-wide studies using questionnaires, interviews, and real-time task observations. Collect multimodal data via motion-capture
-
an emphasis on technology, data science and the humanities. The PRECISE-SG100K is a landmark population cohort study of 100,000 Singaporeans of diverse ethnic background. The cohort has completed recruitment
-
focused on the integration of non-conventional geothermal energy (EGS/AGS) into data centre cooling systems in Singapore, including geothermal-assisted cooling architectures, absorption chilling, heat pumps
-
mathematical modeling framework to find the optimal operation strategy for public transport services with autonomous vehicles Conduct computer programming to verify the efficiency of the designed solution
-
these methods to heart disease modeling using multimodal clinical data. Work with PhD students and research staff to solve related research problems; oversee and report project progress. Job Requirements
-
spatiotemporal systems by combining physics-driven baselines with data-driven correctors. Formulate and solve inverse problems using Physics-Informed Neural Networks and relevant methodologies. Conduct rigorous