191 parallel-and-distributed-computing-"DIFFER" Fellowship positions at Nanyang Technological University
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
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 research on multi-layer metasurfaces for wireless communications, sensing, and computing. Key Responsibilities: Design the multi-layer metasurfaces prototype for wireless communications, sensing
-
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
-
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
-
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
-
. 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
-
, 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