Postdoctoral Fellow AI

Job Description Conduct cutting - edge research on the AI - assisted design and development of self - lubricating polymers and polymer composites for high - temperature tribological applications. Develop machine learning and physics - informed models for predicting friction, wear, thermal stability, and mechanical performance of advanced materials. Design, fabricate, and characterize novel polymeric materials using experimental and computational approaches. Integrate AI/ML techniques with tribological testing, materials informatics, and optimization frameworks to accelerate material discovery. AI - assisted materials design has become a powerful approach for discovering polymers with targeted thermal and functional properties. Publish high - impact research articles and contribute to sponsored research projects. Collaborate with researchers from Mechanical Engineering, Materials Science, and Computer Science disciplines. Key Responsibilities: Develop AI/ML models for material property prediction and inverse material design. Create databases of polymer formulations and tribological performance metrics. Conduct tribological testing under high - temperature conditions. Perform material characterization using microscopy, thermal analysis, spectroscopy, and mechanical testing. Assist in project proposal writing and industry collaborations. Mentor postgraduate and doctoral students working in the project. Desirable Skills: Candidates should possess expertise in one or more of the following: Materials/Tribology Domain Polymer Tribology Self - Lubricating Materials Polymer Composites and Nanocomposites High - Temperature Materials Wear and Friction Analysis Materials Characterization Techniques (SEM, EDS, FTIR, DSC, TGA, DMA) Job Category Research Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.