Postdoctoral Fellows in AI and Computational Biology

The Yang Zhang Lab at the National University of Singapore (NUS) is recruiting two postdoctoral fellows in artificial intelligence and computational biology. The lab is jointly based in the School of Computing, the Yong Loo Lin School of Medicine, and the Cancer Science Institute of Singapore, working at the interface of computer science, structural biology, and biomedical research.

The positions focus on developing next-generation AI methods for biomolecular modeling and AI-driven drug discovery, including protein/RNA folding, structure prediction, and sequence design. The research is method-driven, emphasizing original algorithm/model development (foundation-model architectures integrating sequence, structure, and physical information) rather than applying existing pipelines to standard benchmarks.

Fellows will work in a computationally intensive environment with access to large-scale HPC (hybrid NVIDIA GPU/CPU clusters) and are expected to lead projects from conception through large-scale training and rigorous evaluation.

Develop novel AI/ML algorithms and foundation-model architectures for biomolecular modeling and AI-driven drug discovery.

Design and implement models integrating sequence, structural, and physical information for biomolecular states/interactions.

Lead projects end-to-end: problem formulation, algorithm development, implementation, large-scale training on HPC (GPU/CPU), and rigorous evaluation.

Maintain high-quality, reproducible research code and experimental workflows.

Prepare manuscripts and present research outcomes in relevant venues; contribute to the lab’s AI-for-Science research program.

(Optional/if true) Collaborate with interdisciplinary partners at NUS, including experimental and clinical collaborators when relevant.

PhD (completed or near completion) in computer science, machine learning, biophysics, or a closely related field.

Strong programming skills and ability to develop new models/methods independently.

Demonstrated ability to define research directions, take ownership, and drive projects to completion.

Strong publication record in relevant areas/venues.

Plus (preferred): experience in structural bioinformatics and/or large-scale deep learning.