AI-Driven Polymer Design Scientist for Smart Hydrogels

A*STAR - Agency for Science, Technology and Research; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

A*STAR - Agency for Science, Technology and Research is seeking an AI-Driven Polymer Design Scientist to design and optimise functional polymer systems using AI-enabled approaches, with a focus on stimuli-responsive and hydrogel formulations for biomedical applications.

The role spans polymer chemistry, physical chemistry, and machine learning, contributing to self-driving lab capabilities and high-throughput materials discovery.

Qualifications

• PhD in Materials Science and Engineering or related field.
• Hands-on polymer synthesis, formulation, and characterisation.
• Programming and data analytics with Python/SQL and ML modeling.
• Ability to work in multidisciplinary teams and communicate clearly.

Responsibilities

• Synthesise, formulate, and characterise functional polymers with tunable self-assembly, gelation, and mechanical properties.
• Develop predictive models linking synthesis, processing, formulation, and structure to material behavior.
• Engineer descriptors and features to improve model interpretability and accuracy.
• Establish structure–property relationships using materials characterization to guide design.
• Build data-driven design tools for material selection and optimization across industries.
• Contribute to lab automation, data infrastructure (SQL-based), and integrated ML workflows.
• Prepare technical reports, publications, and disclosures; collaborate across teams and external partners.

Skills

Polymer synthesis

Data analysis

Python

SQL

ML modelling

Communication

Education

PhD in Materials Science and Engineering or related field

Tools

SQL data infra

Job description

A*STAR - Agency for Science, Technology and Research is seeking an AI-Driven Polymer Design Scientist to design and optimise functional polymer systems using AI-enabled approaches, with a focus on stimuli-responsive and hydrogel formulations for biomedical applications.

The role spans polymer chemistry, physical chemistry, and machine learning, contributing to self-driving lab capabilities and high-throughput materials discovery.