40 algorithm-development Fellowship positions at Nanyang Technological University in Singapore
Sort by
Refine Your Search
-
(terrestrial and NTN). The goal of this research is to design and develop algorithms and techniques that adapt to the environment, minimizing signaling overhead associated with channel estimation and enhancing
-
Centre for Advanced Robotics Technology Innovation (CARTIN) is looking for a candidate to join them as a Research Fellow. Key Responsibilities: Develop novel algorithms for multi-agent inverse
-
Developing and integrating AI algorithms into the real development progress Preparing academic publications such as patent applications and research papers Contributing to quarterly and annual report writing
-
The Institute for Digital Molecular Analytics and Science (IDMxS) of the Nanyang Technological University, Singapore, is searching for a Research Fellow (RF) to develop artificial intelligence
-
The Continental-NTU Corp Lab invites applications for the position of Research Fellow. Key Responsibilities: Lead the development of situation awareness, interaction behaviour modelling and decision
-
. The roles of this position include: Development of algorithms to improve memory/sample/time efficiency of LLM training. Development of a workable prototype system with capabilities such as conversational
-
economics Develop state-of-the-art algorithms in algorithmic game theory and fair division Design and conduct experiments to evaluate the algorithm performance Job Requirements: PhD degree in computer science
-
state-of-the-art facilities to work on the following: Developing advanced path planning, search, and exploration algorithms for multi-UAVs systems in unknown and complex 3D environments. Designing
-
, 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