The posting
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%2C-AI-%28School-of-Computing%29/33023-en_GB/?st=937DED9D26CA744C5D0E0D785BD0FB1285657060
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 in developing novel computational solutions to a wide range of applications, building largescale experimental systems, developing theories and policies for effective management of information systems in organizations, 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.
The candidate will conduct research in AI for Science and computational biology, with a focus on developing advanced machine learning methods for biomolecular structure prediction and molecular design. The research will involve multimodal and graph-based representation learning, foundation models, and generative AI for integrating sequence, structural, geometric, and physical information across proteins, nucleic acids, and small molecules. The Research Fellow will develop and evaluate new algorithms, conduct large-scale computational experiments, collaborate with interdisciplinary researchers, and publish research findings in leading journals and conferences.
Qualifications
PhD in Machine Learning, Artificial Intelligence, Computer Science, Applied Mathematics, or a closely related field. Strong background in machine learning and deep learning, with experience in areas such as graph neural networks, multi-view learning, representation learning, transformers, optimization, or generative models. Strong programming skills in Python and experience with modern deep-learning frameworks are required. The candidate should demonstrate strong analytical and problem-solving abilities, research independence, good communication skills, and the ability to work effectively in an interdisciplinary research environment. Prior experience in computational biology is desirable but not essential.



