230 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at Nanyang Technological University
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
contribute to grant proposals and progress reports. Collaborate with interdisciplinary teams within CQT and with external academic and industry partners. Requirements PhD in Physics, Engineering, Computer
-
, machine learning, and life cycle assessment, we aim to create sustainable wearable systems to enhance human well-being. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking
-
maritime transport, marine technology, computer science, or a related field; Excellent programming skills, such as Python, Matlab, C++, or other computer languages; A record of publications in reputable peer
-
optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
-
for active learning. The role will work at the intersection machine learning, high-throughput computation, and inorganic crystalline materials discovery, focusing on accelerating the design and
-
in top-tier conferences and journals Job Requirements: PhD or equivalent in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field. Strong background in IC front-end
-
conferences and journals Job Requirements: PhD or equivalent in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field. Strong background in IC front-end design
-
Research Fellow / Associate Research Fellow / Senior Analyst / Research Analyst (Maritime Security Programme) The S. Rajaratnam School of International Studies (RSIS), a Graduate School of Nanyang
-
researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
-
integration and AI models tailored for fish behaviour, health, and stress signal analysis. Investigate and apply novel machine learning and deep learning techniques for pattern recognition, classification, and