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Research Fellow, AI (School of Computing)

D05 Pasir Panjang, Hong Leong Garden, Clementi New Town, Singapore
Full TimeInformation Technology

Job Description

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%29/33615-en_GB/?st=25BBC90CCE177A25A2E9DB06BD70C918F0610471 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-driven biological modeling, with a focus on generative modeling, representation learning, multimodal biological data integration, and spatially structured molecular systems. The candidate will develop computational methods for complex biological data, implement scalable deep learning pipelines, analyze large-scale omics datasets, and contribute to manuscripts, software, and collaborative research projects. Qualifications Ph.D. in computer science, artificial intelligence, bioinformatics, computational biology, or a related field. Strong experience in deep generative modeling, representation learning, scientific programming, spatial omics analysis, and multimodal biological data integration. Demonstrated ability to publish high-impact research and work independently on challenging computational biology problems.

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First seen: July 6, 2026
Last updated: July 20, 2026