AI Scientist for RNA Drug Discovery & Deep Learning

A*STAR Research Entities (A*STAR); Singapore; On-site; SGD 120,000 - 160,000; Full time

Benefits offered by this job

Fully funded position

Professional development opportunities

Access to NSCC HPC clusters

Interdisciplinary research environment

Job summary

A*STAR Research Entities (A*STAR) invites applications for a PhD-level role focused on AI-driven RNA structure prediction within the AIDD project. The successful candidate will develop deep learning models, integrate chemical reactivity data, and leverage high-performance computing to advance RNA-targeting drug discovery.

Collaboration across biology and chemistry teams is essential. The position emphasizes independent research, publication quality work, and contribution to an interdisciplinary

Qualifications

• PhD required in a science/engineering field.
• Proven experience in deep learning research and development.
• Publication record at top-tier AI conferences (e.g., NeurIPS, ICML, CVPR).
• Strong Python programming and software engineering skills.
• Experience with biomolecules and/or high-performance computing is a plus.
• Structured, independent, proactive and collaborative working style.

Responsibilities

• Develop deep learning-based models for RNA structure prediction.
• Analyze chemical reactivity experimental data.
• Incorporate chemical reactivity data into the structure prediction pipeline.
• Run large-scale training on high-performance computing infrastructure.
• Perform model finetuning and hyperparameter optimization.
• Evaluate models on experimental data.

Skills

Deep learning research

Python programming

Publication track record

Collaborative working style

Education

PhD in computer science, computational biology, computational chemistry, applied mathematics, physics, or related field

Job description

A*STAR Research Entities (A*STAR) invites applications for a PhD-level role focused on AI-driven RNA structure prediction within the AIDD project. The successful candidate will develop deep learning models, integrate chemical reactivity data, and leverage high-performance computing to advance RNA-targeting drug discovery.

Collaboration across biology and chemistry teams is essential. The position emphasizes independent research, publication quality work, and contribution to an interdisciplinary