AI Scientist, Materials Science & Chemistry, IMRE

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 120,000 - 210,000; Full time

Job summary

A*STAR RESEARCH ENTITIES in Singapore is seeking an AI Scientist for AI for Ceramic Materials within the MARVEL / CERAMIT programme. You will design AI/ML models guiding experiments and learning from data, bridging AI with real-world materials testing.

You will collaborate with materials scientists, curate datasets, and help advance high-throughput experimentation and SDL workflows. PhD required with strong Python/ML capability.

Qualifications

• PhD in Materials Science & Engineering, Ceramic Engineering, Chemical Engineering, Computer Science, Data Science, Physics or related disciplines.
• Strong experience in AI/ML or ceramic/materials science, bridging both fields.
• Proficiency in Python and ML libraries such as PyTorch, TensorFlow or Scikit-learn.

Responsibilities

• Develop and apply AI/ML models for ceramic materials discovery and process optimisation.
• Build data-driven relationships between composition, processing, microstructure and properties.
• Create and curate high-quality ceramic materials datasets from diverse sources.
• Apply ML techniques including active learning, Bayesian optimisation and AI agents.
• Collaborate with scientists to translate challenges into AI-driven solutions.
• Design experiments to validate AI predictions and improve models.
• Integrate AI models with Self-Driving Laboratory workflows.
• Develop closed-loop workflows: AI Prediction → Experiment → Data → Model Update.

Skills

AI/ML experience

Python

Education

PhD in Materials Science & Engineering or related

Tools

PyTorch

TensorFlow

Scikit-learn

Job description

We are seeking a highly motivatedAIScientist – AI for Ceramic Materialsto join the MARVEL / CERAMIT programme, an interdisciplinary initiative combiningArtificial Intelligence, Materials Science, high-throughput experimentation and Self-Driving Laboratories (SDL)to accelerate ceramic materials discovery and process optimisation.

This is an opportunity to work at the intersection ofAI and real-world materials experimentation, developing AI models that are not only predictive, but can guide the next experiment and continuously learn from new experimental data.

Key Responsibilities

• Develop and applyAI/ML modelsfor ceramic materials discovery, property prediction and process optimisation.
• Build data-driven relationships betweencomposition, processing, microstructure and material properties.
• Develop and curate high-quality ceramic materials datasets from experimental, literature and computational sources.
• Apply techniques such asmachine learning, deep learning, active learning, Bayesian optimisation and AI agents.
• Collaborate with materials scientists to translate real-world materials challenges into AI-driven solutions.
• Design experiments to validate AI predictions and improve model performance.
• Integrate AI models withSelf-Driving Laboratory and automated experimentation workflows.
• Develop closed-loop workflows:AI Prediction → Experiment → Characterisation → Data → Model Update.
• Contribute to high-impact publications, intellectual property, technology development and industry collaborations.
• Mentor junior researchers and contribute to a multidisciplinary research environment.

Requirements

• PhD inMaterials Science & Engineering, Ceramic Engineering, Chemical Engineering, Computer Science, Data Science, Physicsor related disciplines.
• Strong experience inAI/ML or ceramic/materials science, with a strong interest in bridging both fields.
• Proficiency inPythonand relevant scientific/ML libraries such as PyTorch, TensorFlow, Scikit-learn or equivalent.
• Strong analytical, problem-solving and scientific communication skills.
• Ability to work independently as well as collaboratively across disciplines.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.