AI ML Intern for Computational Fluid Dynamics (6 months)

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At Cadence we hire and develop leaders and innovators who want to make an impact on the world of technology.

Job Title: AI/ML Internship for CFD applications in automotive aerodynamics

Location: Brussels Belgium

Duration: 6 months

Reports to: Software Engineering Director

Job Overview:

Computational Fluid Dynamics (CFD) is critical in engineering but expensive at industrial scales especially for automotive applications. Emerging machine learning surrogates promise faster predictions; their strengths differ depending on data availability physics constraints and geometry complexity.

This AI/ML internship will benchmark data-only and physics-informed approaches for steady RANS external aerodynamics and evaluate whether adding global geometric context to an existing surface prediction workflow improves results.

The goal of this work is to assess whether nextgeneration ML surrogates can significantly accelerate external aerodynamics workflows enabling faster design exploration in the automotive sector.

Job Responsibilities:

You will work with existing highquality CFD datasets internal geometricprocessing tools and established ML experimentation frameworks to ensure a reproducible and wellsupported workflow.

• Survey the literature on machinelearning surrogates for steady RANS CFD including physicsinformed training and multiscale geometric context.
• Set up datasets and baselines for a reproducible comparison across identical test cases.
• Implement and train a datadriven surrogate for surface quantities.
• Prototype physicsinformed training and compare against dataonly setups.
• Evaluate models across clearly defined metrics (accuracy efficiency physics compliance robustness)

Deliverables:

• Literature survey and design rationale.
• Reproducible benchmarking repository (code configs scripts).
• Technical report and slides summarizing results and recommendations.

Job Qualifications:

• Masters or finalyear bachelors in mechanical or aerospace engineering applied mathematics computer science or related
• Strong Python and modern ML frameworks
• Familiarity with CFD fundamentals (NavierStokes RANS turbulence concepts)
• Experience with geometric data (meshes/point clouds/surfaces)

Additional Skills/Preferences:

• Exposure to physicsinformed ML or operatorstyle models

Cadence is committed to equal employment opportunity and employment equity throughout all levels of the organization. We strive to attract a qualified and diverse candidate pool and encourage diversity and inclusion in the workplace.

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