Research Fellow (Computer Science/Artificial Intelligence/Machine Learning)

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.

Key Responsibilities:

• To conduct independent research in deep learning, large-scale model optimization, and generalization.
• To explore scalable optimization methods for large-scale, distributed, and multi-node collaborative training.
• To conduct theoretical analysis of optimization and generalization to inform the design of practical training algorithms.
• To produce high-quality publications in top-tier machine learning conferences and journals.
• To offer guidance and assistance to students involved in the project.
• To collaborate with academic and industrial partners and perform other duties related to the research program.

Job Requirements:

• A PhD in Computer Science, Artificial Intelligence, Machine Learning, or relevant fields.
• Strong theoretical research capability, particularly in the theoretical analysis of optimization, convergence, stability, and/or generalization of deep learning models.
• Strong background in machine learning optimization, with experience in distributed or multi-node collaborative training; experience in large-scale training is highly desirable.
• Strong publication record in top-tier machine learning conferences and journals, such as ICML, ICLR, NeurIPS, and IEEE TPAMI.
• Demonstrated capability to formulate fundamental research problems, develop novel optimization methodologies, and conduct rigorous theoretical and empirical studies.
• Independent, highly analytical, proactive, and capable of working effectively in a collaborative research environment.

We regret that only shortlisted candidates will be notified.