Materials Scientist

Company Description

Greenlyzer is a Singapore-based deep technology company developing next-generation materials and intelligent energy systems for the emerging AI and electrification era.

We are building the Green Moving Grid, a distributed and AI-orchestrated energy architecture designed to augment conventional centralized power infrastructure with modular hydrogen-based energy networks. Through our Alpha Energy System platform, we integrate advanced membrane materials, hydrogen production and storage technologies, fuel-cell power systems, and real-time energy orchestration software to enable resilient, low-carbon power delivery for mission-critical applications.

Our technologies are designed to support the rapidly growing energy demands of AI data centers, industrial electrification, EV charging infrastructure, and distributed energy systems. By combining advanced materials science, electrochemistry, and AI-enabled optimization, we aim to accelerate the transition toward intelligent, decentralized, and sustainable energy infrastructure.

Position Summary

We are seeking a Materials Scientist to join the development of next-generation polymer and membrane materials for advanced electrochemical and energy-transition applications.

This role requires deep expertise in polymer chemistry, membrane materials, and structure–property engineering, combined with practical experience applying AI/ML, materials informatics, or data-driven methodologies to accelerate material discovery, optimization, and scale-up.

The successful candidate will provide technical leadership across polymer design, synthesis strategy, membrane engineering, and advanced materials development, while spearheading the integration of AI-enabled and data-driven methodologies into next-generation energy materials R&D workflows.

Key Responsibilities

• Lead technical strategy for advanced polymer and membrane material development.
• Design polymer architectures, synthesis pathways, functionalization strategies, and structure–property optimization approaches.
• Guide rapid material iteration, characterization, and performance validation activities.
• Drive membrane fabrication and process scale-up efforts including coating, casting, lamination, and process optimization.
• Apply AI/ML, statistical modeling, or materials informatics approaches for predictive materials development and formulation optimization.
• Develop modern data-driven R&D methodologies integrating experimental and computational workflows.
• Support technical problem-solving, failure analysis, IP generation, and long-term technology roadmap development.
• Mentor and guide multidisciplinary R&D teams across chemistry, materials science, and process engineering activities.

Qualifications

• Post-graduate Degree (MS or PhD) in Polymer Science, Materials Science, Chemical Engineering, Chemistry, or related disciplines.
• 5+ years of industrial or advanced applied R&D experience in polymers, membranes, coatings, or advanced functional materials.
• Strong expertise in polymer synthesis, functionalization chemistry, and structure–property relationships.
• Experience with membrane materials, electrochemical materials, or related systems.
• Experience supporting material development from laboratory through pilot-scale or manufacturing environments.
• Hands-on experience applying data-driven methodologies to materials development, including structure–property modeling, formulation optimization, experimental design, predictive materials informatics, or high-throughput experimentation.
• Familiarity with AI/ML-assisted materials R&D and scientific computing workflows is highly desirable.