Digital Twin Modeling for Structures JRF Position

About Internship

Assistant Professor from Indian Institute of Technology - Indian School of Mines, Dhanbad (IIT-ISM Dhanbad), is accepting candidates interested in the field of Physics, in the research area of Digital Twin for Structures.

The pi-DUST (Physics-Informed Data-driven Modeling and Uncertainty Quantification with Application to Structural Twins) project at IIT (ISM) Dhanbad, funded under the ANRF-ECRG program, focuses on advancing digital twin technologies for engineering structures through the integration of computational mechanics, artificial intelligence, uncertainty quantification, and physics-informed data-driven modeling. As a Research Intern/Junior Research Fellow, you will work in an interdisciplinary research environment alongside experts in computational engineering and collaborate with researchers from internationally renowned institutions, including Texas A&M University and TU Delft. You will contribute to the development of computational models, AI-enabled structural analysis techniques, experimental validation, and digital twin solutions for real-world engineering applications. The role offers hands-on experience in finite element modeling, structural dynamics, solid mechanics, uncertainty quantification, and AI/ML for structural systems, using tools such as Python, ANSYS, COMSOL, MATLAB, and image processing frameworks. Selected candidates will also have opportunities to contribute to research publications, open-source software development, and industry-relevant engineering solutions, while building a strong international research profile in the rapidly evolving field of computational engineering and structural digital twins. This opportunity is ideal for candidates pursuing or holding a degree in Mechanical Engineering, Civil Engineering, Aerospace Engineering, Applied Mechanics, Applied Mathematics, Computational Engineering, or related disciplines, with a strong interest in research, computational modeling, simulation, and artificial intelligence for engineering applications.