Intern – CAE & AI-Driven Simulation Workflows

Trisim Technologies, founded in 2016, is a technology consulting firm based in Pune, India. The company provides high-end consulting services to organizations in various fields of emerging and cutting-edge technology. We have worked with multiple clients in the fields of engineering simulations (CFD/CAE), Data Science, software customization along with in-house R&D efforts in modelling and simulation. About the Role We are seeking a research-driven intern to explore how open-source CAE simulation tools and modern AI/ML libraries—including NVIDIA Modulus, NVIDIA Omniverse physics APIs, TensorRT/cuDNN, and Julia’s Dyad.jl—can be combined to create next-generation industrial simulation workflows. The goal is to evaluate current technologies and develop a pilot end-to-end workflow demonstrating the value of hybrid physics + AI approaches for engineering design. Responsibilities -Explore AI/ML frameworks relevant to physics: • NVIDIA Modulus, Omniverse, TensorRT, cuDNN • Julia Dyad.jl and SciML libraries • PyTorch, TensorFlow, JAX, PINNs, DeepONets, GNOs - Identify industrial workflows (meshing automation, simulation pipelines, surrogate models, hybrid physics-AI workflows). - Build a prototype CAE+AI workflow. - Assess open-source CAE tools: OpenFOAM, FEniCS, Code_Aster, CalculiX, SU2, Salome, ParaView, Elmer. - Document architecture, results, and scalability potential. - Present findings to technical and business stakeholders. Qualifications • Master’s degree (or in progress) in Mechanical/ Aerospace Engineering, Computational Science, Applied Physics/Mathematics, with knowledge of Data Science, or similar. • Understanding of numerical methods, PDEs, and simulation concepts. • Proficiency in Python. • Experience with PyTorch or TensorFlow; exposure to JAX is a plus. • Ability to learn independently and document findings clearly. Preferred Skills • Exposure to NVIDIA Modulus or physics-ML. • Experience with Julia and scientific ML (Dyad.jl, SciML). • Familiarity with Linux, Docker, Git. • Interest in AI-accelerated engineering, HPC, cloud-based simulation. • Understanding of engineering domains (thermal, structural, fluids) What You Will Gain • Hands-on experience with leading open-source CAE and physics-ML technologies. • Experience designing digital-engineering workflows. • A working prototype showcasing hybrid simulation + AI. • Exposure to cutting-edge research and industrial practices. • Opportunities to publish findings or present to leadership.