44 machine-learning "https:" "https:" "https:" positions at Nanyang Technological University
Sort by
Refine Your Search
-
computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
-
middleware (e.g., ROS, MoveIt) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g
-
Responsibilities: Electrochemical process on interface phenomena Battery testing under different conditions Simulation of scaled up process. Interface with machine learning group on data base set up Battery safety
-
of servers and assistance in network setup in a testbed building. Data collection from BMS and thermal and occupancy sensors, and machine learning based analysis. Daily system maintenance for the servers and
-
in the 2025 QS World University Rankings by Subjects. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Postdoctoral Fellow to advance cutting-edge research in the security
-
analytics and machine learning techniques. Familiar with software implementation. Good written and oral communication skills. Interpersonal skill (e.g. Ability to work independently / develop solutions under
-
. Publication of research papers and IPs. To assist project PI to coach research students. Job Requirements: A Bachelor’s degree in relevant fields with past experience in embedded system, machine learning and
-
accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large
-
workflows for processor and accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform
-
, 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