Research Fellow (Electrical and Computer Engineering/Computer Science/AI)

Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a leading college that is known for its excellent curriculum, outstanding and impactful research, and world-renowned faculty.

A hot bed of cutting-edge technology and groundbreaking research, the College aims to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an exciting place to learn and grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing.

MMLab@NTU at CCDS is a research lab at Nanyang Technological University focused on advancing computer vision, multimodal AI, generative AI, and embodied AI. Founded in 2018, the lab has grown into a vibrant research group with around 40 members comprising faculty, research staff, and PhD students. Our members develop both foundational methods and practical systems, with recent research covering areas such as large multimodal models, generative intelligence, 3D content creation, scene understanding, and efficient vision models for real-world deployment.

We are seeking a Research Fellow to join MMLab@NTU at the College of Computing and Data Science for a Tier 2 research project in computer vision and multimodal learning. Key responsibilities include:

• →Conduct research in computer vision, vision-language models and generative AI.
• →Develop methods for AI memory.
• →Build datasets and evaluate robustness, generalisation and hallucinations in visual models.
• →Publish research findings and prepare technical reports and reproducible implementations.
• →Mentor students and collaborate with the research team to deliver project milestones.

Job Requirements:  

• →PhD in Electrical and Computer Engineering, Computer Science, AI or a related field.
• →Strong background in computer vision, deep learning and vision-language models.
• →Research experience in generative AI, foundation models and AI memory.
• →Strong publications in leading computer vision or machine learning venues.
• →Experience implementing and fine-tuning deep learning models, using frameworks such as PyTorch.
• →Strong experimental, analytical and scientific writing skills.
• →Ability to work independently, collaborate effectively and mentor students.

We regret that only shortlisted candidates will be notified.