Research Fellow in Artificial Intelligence and Computational Biology

2 weeks ago

Singapore beBeeArtificialIntelligence Full time $90,000 - $120,000
Research Fellow in AI and Computational Biology

We are seeking highly motivated individuals to fill two Research Fellow positions at the intersection of artificial intelligence (AI) and computational biology/medicine. Our group focuses on developing next-generation AI algorithms and foundation-model strategies for protein and RNA structure prediction, de novo protein/peptide design, protein–ligand docking and virtual screening, and AI-driven oncology therapeutics.

The ideal candidate will have a strong background in computer science, AI/ML, or computational biology, with expertise in deep learning frameworks such as PyTorch, JAX, or TensorFlow. The successful candidate will have demonstrated ability in algorithm/model development and a solid publication record, including first-author papers in leading journals or conferences.

This is an excellent opportunity for talented researchers to join a vibrant interdisciplinary environment across the NUS School of Computing, Yong Loo Lin School of Medicine, and Cancer Science Institute. Collaborations with wet-lab and clinical collaborators are encouraged, and the lab provides ample research resources, including generous consumables, publication support, and conference travel funding.

Key Responsibilities:
  • Lead independent research projects in one or more of the following areas: Foundation models and deep learning for biological sequences and structures, Protein and RNA 3D structure prediction and dynamics modeling, De novo protein/peptide design and sequence-to-function modeling, Molecular docking, virtual screening, and generative design for drug discovery.
  • Develop and implement novel algorithms and reproducible code, curate datasets, and conduct large-scale training on GPU clusters.
  • Collaborate in an interdisciplinary environment, mentor junior researchers and students, and disseminate results through high-impact publications and presentations.
Required Qualifications:
  • PhD (completed or close to completion) in Computer Science, AI/ML, Computational Biology, Biophysics, or a related field.
  • Strong programming skills (e.g., Python, C/C++, scientific computing) and practical experience with deep learning frameworks.
  • Demonstrated ability in algorithm/model development and a solid publication record, including first-author papers in leading journals or conferences.
  • Excellent communication skills and a strong commitment to interdisciplinary teamwork.
Preferred Qualifications:
  • Background in structural modeling, bioinformatics, or cheminformatics.
  • Experience with large-scale model training, distributed computing, or GPU optimization.
  • Prior research in protein/RNA modeling, molecular docking, or generative design.
Benefits:
  • Internationally competitive stipend and benefits.
  • Ample research resources, including generous consumables, publication support, and conference travel funding.
  • Cutting-edge compute power: shared access to HPC and NVIDIA H100 GPU clusters, high-memory nodes, and modern ML tooling.
  • Strong mentorship and visibility, with opportunities for first-/co-first-author publications in top-tier venues, conference presentations, and support for fellowship or grant applications.

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