RNA-Targeting AI Scientist for Drug Discovery

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 6,000 - 9,000; Full time

Benefits offered by this job

Fully funded position

Conferences & career development

Access to NSCC HPC clusters

Collaborative interdisciplinary team

Initial 1-year contract with potential

Job summary

A postdoctoral researcher position at A*STAR RESEARCH ENTITIES focuses on developing deep learning models for RNA structure prediction. You will analyze chemical reactivity data and integrate it into the prediction pipeline, using large-scale HPC resources for training and tuning.

Applicants should hold a PhD in a relevant field and have a strong publication track record in AI. Collaboration across biology, chemistry, and computation is expected in a dynamic research environment.

Qualifications

• PhD in computer science, computational biology, computational chemistry, applied mathematics, physics, or related field.
• Proven experience in deep learning research and development.
• Publication record at top-tier AI conferences (e.g., NeurIPS, ICLR, ICML, CVPR, ICCV, ACL).
• Strong Python programming and software engineering skills.

Responsibilities

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

Skills

Python programming

Deep learning

Biomolecules

HPC experience

Education

PhD in computer science/bi computational biology/related field

Tools

PyTorch

TensorFlow

Job description

A postdoctoral researcher position at A*STAR RESEARCH ENTITIES focuses on developing deep learning models for RNA structure prediction. You will analyze chemical reactivity data and integrate it into the prediction pipeline, using large-scale HPC resources for training and tuning.

Applicants should hold a PhD in a relevant field and have a strong publication track record in AI. Collaboration across biology, chemistry, and computation is expected in a dynamic research environment.