Research Fellow (Computer Science)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Computer-Science%29/33598-en_GB/?st=C53FA7DB0138A36658A5F1588C79AC9FA35EE764

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for the position of Research Fellow  in the Department of Computer Science, School of Computing (SoC). SoC is strongly committed to research excellence in all its dimensions: Searching for fundamental results and insights, developing novel computational solutions to a wide range of applications, building large-scale experimental systems and improving the well-being of society. We seek to play an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems

We are seeking a highly motivated Postdoctoral Research Fellow to conduct cutting-edge research in machine learning and artificial intelligence. The successful candidate will develop novel algorithms, publish in leading AI conferences and journals, collaborate with students and international research partners, and contribute to research proposals and open-source software. The position offers opportunities to work on topics such as deep learning theory, large language models, optimization, reinforcement learning, generative AI, and trustworthy AI.

Only shortlisted candidates will be notified.

Job Requirements

• Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, or a closely related field.
• Strong publication record in top-tier AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI, or equivalent).
• Strong mathematical background in machine learning, optimization, probability, or statistics.
• Ability to conduct independent research while collaborating effectively in a multidisciplinary team.