Scientist, Materials Science & Chemistry, IMRE

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

AI- Driven Polymer Design Scientist

We are seeking a motivated Research Scientist to design and optimise functional polymer systems using AI-enabled approaches, with an initial focus on stimuli-responsive and hydrogel formulations for biomedical and delivery applications, expanding into polymers for other key industry applications. The role bridges polymer chemistry, physical chemistry, and machine learning, contributing to the development of self-driving lab and high-throughput materials discovery capabilities.

Job Description

We are seeking a motivated Research Scientist to design and optimise functional polymer systems using AI-enabled approaches, with an initial focus on stimuli-responsive and hydrogel formulations for biomedical and delivery applications, expanding into polymers for other key industry applications. The role bridges polymer chemistry, physical chemistry, and machine learning, contributing to the development of self-driving lab and high-throughput materials discovery capabilities.

Job Responsibilities

• Synthesise, formulate, and characterise functional polymers with tunable self-assembly, gelation, and mechanical properties.
• Develop predictive (classification and regression) models that relate synthesis, processing conditions, formulation, and structure to material behaviour and performance.
• Engineer descriptors and features that improve model interpretability and predictive accuracy.
• Establish structure–property relationships using materials characterisation to guide formulation design.
• Build data-driven design tools that translate empirical formulation knowledge into material selection and optimization for various industrial applications.
• Contribute to lab automation, data infrastructure (SQL-based), and integrated experimental–ML workflows for accelerated discovery.
• Prepare technical reports, publications, and disclosures; collaborate across teams and with external partners.

Job Requirements

• PhD degree in Materials Science and Engineering, Polymer Chemistry, Chemical Engineering, Chemistry, or a related field.
• Hands-on experience in polymer/materials synthesis, formulation, and characterisation.
• Programming and data-analytics capability (e.g. Python, SQL), including ML model development and validation.
• Ability to work independently and within a multidisciplinary team, with strong communication and documentation skills.

Preferred Qualifications

• Experience integrating experimental data with machine learning for materials design.
• Familiarity with polymers, polymers used in advanced packaging and advanced manufacturing, hydrogels, and drug-delivery systems.
• Exposure to lab automation, high-throughput experimentation, or self-driving lab concepts.
• Track record of publications and/or contributions to intellectual property.