Mechanical Intern

Job Title

Mechanical Modeling & Simulation Automation Intern

Job Summary

We are seeking a highly motivated Mechanical Modeling & Simulation Intern to support the development of advanced simulation workflows for mechanical systems using FEA, CFD, and FSI methodologies.

The role focuses on building automated, scalable simulation frameworks using ANSYS tools and PyAnsys (open-source Python libraries) to improve efficiency, repeatability, and insight generation for R&D applications.

The intern will work closely with engineering teams to translate physical problems into computational models, automate simulation workflows, and contribute to next-generation data-driven and AI-enabled simulation processes.

This position is ideal for postgraduate students with strong foundations in mechanics and/or fluid dynamics, combined with an interest in programming, numerical methods, and simulation automation.

Key Responsibilities

• Develop and execute simulations in one or more domains:
  • Finite Element Analysis (FEA) (structural, thermal, fatigue)
  • Computational Fluid Dynamics (CFD) (flow, heat transfer)
  • Fluid-Structure Interaction (FSI) (optional/advanced)
• Build physics-based models aligned with real-world engineering problems
• Perform parametric and sensitivity studies

Workflow Automation (Core Requirement)

• Develop automated simulation workflows using:
  • PyAnsys (PyMAPDL, PyMechanical, PyFluent, PyDPF, etc.)
  • Python-based scripting
• Create reusable pipelines for:
  • Geometry setup
  • Meshing
  • Solver execution
  • Post-processing of results
• Improve efficiency of repeated simulation tasks and studies

Tool & Framework Development

• Contribute to development of internal simulation tools and frameworks
• Integrate simulation workflows with:
  • Data processing pipelines
  • Optimization or AI/ML workflows (where applicable)
• Standardize modeling approaches for R&D usage

Analysis & Interpretation

• Analyze simulation results and extract engineering insights
• Validate results against analytical models or known benchmarks
• Identify key design drivers and recommend improvements

Collaboration & Documentation

• Work closely with cross-functional engineering teams
• Document workflows, scripts, and simulation methodologies
• Present findings in a clear and structured manner

Required Qualifications

• Currently pursuing or recently completed Postgraduate degree (M.Tech / MS / MSc / equivalent) in:
  • Mechanical Engineering
  • Aerospace Engineering
  • Computational Engineering
  • Applied Mechanics or related fields

Technical Skills

• Core Domain Strength (At least one required)
  • Strong fundamentals in:
    • FEA (stress, deformation, thermal analysis)
    • OR
    • CFD (fluid flow, turbulence basics, heat transfer)

Simulation Tools

• Experience with:
  • ANSYS Mechanical / Fluent / CFX or similar tools

Programming & Automation

• Proficiency in:
  • Python (mandatory)
• Exposure to:
  • PyAnsys (preferred)
  • Scripting APIs for simulation tools

Analytical & Computational Skills

• Understanding of:
  • Numerical methods (FEM, FVM basics)
• Ability to:
  • Translate physical systems into computational models
• Strong problem-solving and logical reasoning skills

Preferred Qualifications (Nice to Have)

• Experience with:
  • FSI simulations
  • Optimization or parametric design studies
• Familiarity with:
  • AI/ML workflows in engineering simulations
  • Data processing libraries (NumPy, Pandas, Matplotlib)
• Exposure to:
  • HPC environments or batch simulation workflows

What the Intern Will Gain

• Hands-on experience with industry-grade simulation tools (ANSYS ecosystem)
• Exposure to automation of engineering workflows using Python
• Opportunity to work on real-world FEA/CFD/FSI problems
• Experience in building next-generation simulation pipelines (AI + automation)
• Mentorship in computational mechanics and R&D problem solving

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.