177 parallel-and-distributed-computing Fellowship positions at Nanyang Technological University in Singapore
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
research, quantum technologies, artificial intelligence, advanced communications and cybersecurity capabilities. The work will be in joint collaboration with the NRF CREATE programme Singapore Aquaculture
-
The NTU AI-for-X Postdoctoral Fellowship (AI4X-PDF), jointly supported by Nanyang Technological University (NTU) and Singapore’s National Research Foundation (NRF), is a prestigious programme
-
techniques (especially program synthesis) to improve the explainability and robustness of AI models Participating in co-operation with Continental’s development team Interacting with Continental business areas
-
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
-
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
-
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
-
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
-
research, quantum technologies, artificial intelligence, advanced communications and cybersecurity capabilities. The work will be in joint collaboration with the NRF CREATE programme Singapore Aquaculture
-
, 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
-
, 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