Position Overview
The Computational Modeling Team develops advanced engine and propulsion technologies using state-of-the-art digital tools, applying AI and simulation-based product development to accelerate the design of clean, efficient, and sustainable transportation technologies. The graduate intern will work alongside research scientists to advance AI-driven automation within our CFD-in-the-loop design optimization framework, contributing ongoing projects.
Education and Qualifications
- Currently enrolled in a graduate program (MS or PhD) at the time of application and throughout the internship
- Computer Science, Mechanical or Automotive Engineering preferred
- Authorized to work in the U.S. or able to obtain authorization by the program start date (CPT/OPT approval required where applicable)
Preferred Skills and Experience
- Programming proficiency in Python; familiarity with C/C++ a plus
- Hands-on CAD and geometry modeling expertise (e.g., SolidWorks, CATIA, NX, or open-source CAD kernels); meshing and CFD pre-processing experience
- Design of experiments, surrogate modeling, Gaussian processes, Bayesian optimization, active/adaptive learning, and optimization algorithms
- Exposure to CFD tools (e.g., CONVERGE, ANSYS Fluent, STAR-CCM+) and HPC environments
- Experience with machine learning frameworks (PyTorch, scikit-learn) and LLM-based coding agents
- Strong analytical, documentation, and communication skills; able to work collaboratively in a team research environment
Opportunities eligible for internship course credit (credits earned), please check with your Academic Advisor or University.
Skills Required
- Currently enrolled in a graduate MS or PhD program at the time of application and throughout the internship
- Computer Science, Mechanical Engineering, or Automotive Engineering background
- Authorized to work in the United States or able to obtain authorization by the program start date
- CPT or OPT approval where applicable
- Programming proficiency in Python
- Familiarity with C or C++
- Hands-on CAD and geometry modeling expertise
- Meshing and CFD pre-processing experience
- Experience with design of experiments, surrogate modeling, Gaussian processes, Bayesian optimization, active or adaptive learning, and optimization algorithms
- Exposure to CFD tools such as CONVERGE, ANSYS Fluent, or STAR-CCM+
- Experience with HPC environments
- Experience with machine learning frameworks such as PyTorch or scikit-learn
- Experience with LLM-based coding agents
- Strong analytical, documentation, and communication skills
- Ability to work collaboratively in a team research environment
What We Do
We’re a leading producer of the energy and chemicals that drive global commerce and enhance the daily lives of people around the globe by continuing delivering an uninterrupted supply of energy to the world. Our resilience and agility has built one of the world’s largest integrated energy and chemicals companies. And we are part of the global effort toward building a low carbon economy. Our horizon has never been clearer.
