Werkstudent für Scientific Computing & Machine Learning (d/m/w)
Core
Supporting Flight Physics Capabilities by bridging classical engineering with modern data science to make next-generation aircraft more efficient, sustainable, and intelligent.
Role type
Scientific Computing & Machine Learning Werkstudent (part-time)
Builds
Scientific computing templates, Reduced Order Models (ROMs), surrogate modeling, data processing pipelines, and MLOps tools for aerodynamics.
Domain
Aerospace engineering / Flight physics / Scientific computing
Deliverable
production ML models | product features | infrastructure
Required skills
Python, NumPy, SciPy, Scikit-learn, Machine Learning fundamentals, Scientific Computing concepts, MLOps, High-Performance Computing (HPC), Cloud technologies
Preferred skills
Cython, C/C++, Julia, CUDA, PyTorch, TensorFlow, XGBoost, MLflow, Kubeflow, Amazon SageMaker, AWS, Google Cloud Platform
Responsibilities
Develop and implement templates, best practices, and documentation for Scientific Computing and MLOps; Improve and maintain internal libraries for technical calculations and ML with focus on refactoring; Build and extend MLOps tools and automation scripts; Create clear documentation including How-to-Guides and architecture overviews.
Seniority
Student (part-time, 18 hours/week)