11 computer-vision-and-machine-learning Fellowship positions at Nanyang Technological University
Sort by
Refine Your Search
-
advance research in computer vision, machine learning, and/or robotics for the digitalization, monitoring, and automation of civil infrastructure. The role will focus on developing innovative methodologies
-
Language Models (MLLMs) and their agentic implementations. Develop and benchmark novel adversarial attacks and defense strategies, focusing on the intersection of computer vision, natural language processing
-
: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
-
mathematical modeling framework to find the optimal operation strategy for public transport services with autonomous vehicles Conduct computer programming to verify the efficiency of the designed solution
-
research grants in the above areas Job Requirements: A PhD degree in Computer Science, Data Science, Engineering, or a related field. Research experience in Computer Vision, Image Processing, Multimedia
-
Intelligence, or a closely related discipline. Strong research background in AI and machine learning, with a focus on efficient or accelerated models. Proven experience with model compression techniques, such as
-
graduate students. Job Requirements: Ph.D. in Electrical Engineering, Computer Science, Statistics, or other related fields. Familiarity with machine learning and computer vision frameworks. Good written and
-
teamwork and verbal, written communication skills In-depth knowledge of computer vision and deep learning Demonstrated capability to conduct innovative research We regret that only shortlisted candidates
-
: Develop and apply new machine learning and computer vision methods such as large-language models and vision-language models for high-throughput analysis of video data. For NeuroAI focus: Apply data-driven
-
equivalent. Strong background in machine learning and computer vision. Prior experience in data-efficient classification, synthesis, and detection is preferable. Strong publication records in top-tier machine