Machine Learning CFD Engineer (Student)

Quick Facts

• Role: Machine Learning CFD Engineer (Student)

• Focus: Data-driven machine learning using 3D CFD simulation data for surrogate/meta models

Description

You will program machine learning algorithms in Python and combine modern ML methods with simulation data from 3D CFD. You will analyze and develop meta-models based on CFD simulations of compressors, creating efficient data-based models for complex flow phenomena. The goal is to reduce the computational effort of numerical optimization while maintaining model accuracy.

Responsibilities

• Program machine learning algorithms in Python

• Connect modern machine learning methods with simulation data from 3D CFD

• Analyze and develop meta-models based on performed CFD simulations of compressors

• Create efficient, data-driven models to represent complex flow processes

• Reduce computational cost of numerical optimization with consistent model accuracy

Requirements

• Studying engineering, computer science, physics, or a related field

• Interest in data-driven optimization methods

• Basic understanding of numerical simulation and thermodynamic processes or fluid mechanics or heat transfer

• Experience with Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn)

• Analytical thinking and structured working style

Benefits

• Barrier-free workplace support

• Occupational physician

• Bridge day rule

• Company laptop

• Flexible working hours

• Health initiatives

• Good public transport connections

• Canteen

• Free drinks

• Employee bonuses

• Employee discounts

• Parking

• Supportive, trust-based management culture