Job

• 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)