Generative AI Scientist for Drug Discovery & Chemistry

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

A leading research institution in Singapore is seeking a computational scientist to develop AI models for ligand discovery. The role involves collaborating with multidisciplinary teams and contributing to the advancement of computational drug discovery. Candidates should possess a Master or PhD in a relevant discipline and have strong knowledge in chemistry, cheminformatics, and structural biology. Proficiency in machine learning frameworks is essential. This opportunity offers a dynamic research environment and the chance to work on cutting-edge techniques.

Qualifications

• Master or PhD degree in a relevant field.
• Passionate about science and research.
• Experience with generative models.
• Ability to work independently and in a team.

Responsibilities

• Develop and implement AI-driven models for ligand discovery.
• Collaborate with multidisciplinary teams.
• Contribute to advancing computational drug discovery capabilities.
• Stay informed on AI and molecular modeling developments.
• Communicate findings to scientific teams and stakeholders.

Skills

Machine learning frameworks (e.g. PyTorch, TensorFlow)

Developing generative models

Chemistry knowledge

Cheminformatics knowledge

Structural biology knowledge

Molecular dynamics simulations

Docking software experience

Excellent written and oral communication

Education

Master or PhD degree in life sciences, chemistry, computational biology, or related discipline

Job description

A leading research institution in Singapore is seeking a computational scientist to develop AI models for ligand discovery. The role involves collaborating with multidisciplinary teams and contributing to the advancement of computational drug discovery. Candidates should possess a Master or PhD in a relevant discipline and have strong knowledge in chemistry, cheminformatics, and structural biology. Proficiency in machine learning frameworks is essential. This opportunity offers a dynamic research environment and the chance to work on cutting-edge techniques.