Working Student Data Science / AI (m/f/d)
Work on AI-based test algorithms and anomaly detection – with real industrial data sets from over 180 inline systems.
Your role.
More than a data playground – real industry.
You don't work with synthetic toy datasets but with real acoustic signals from brake discs, e-drives, sintered parts and more. You support our R&D team on classic ML, anomaly detection and deep learning approaches for acoustic test technology.
Ideal for students of computer science, mathematics, physics or electrical engineering interested in signal processing and machine learning. 15–20 h/week, Pfinztal with home office option.
What you'll do.
- Data preparation and feature engineering on acoustic time and frequency signals
- Train, evaluate and tune classic classifiers (SVM, random forest, GBM)
- Contribute to anomaly detection (autoencoders, one-class SVM, statistical methods)
- Validate models against customer KPIs (slip rate, false rejects)
- Documentation, reproducibility, small contributions to the SonicTC model pipeline
What you bring.
- Ongoing studies in computer science, mathematics, physics, EE or similar
- Solid Python, ideally NumPy / scikit-learn / PyTorch
- Basic understanding of signal processing (FFT, filters, spectrograms) – or eager to learn
- Clean, reproducible work (Git, virtual environments, notebooks → modules)
- At least 12 months of remaining study time, 15–20 h/week available
What you can expect from us.
Real data
Industrial signals from production – no exercise datasets.
Mentoring
Experienced R&D team in acoustics, DSP and ML – with Fraunhofer roots.
Flexibility
Studies come first – exam phases are respected.
Perspective
Option for thesis (Bachelor / Master) and direct entry afterwards.
Modern setup
Own laptop, GPU server, your own desk in the team.
Compensation
Fair, market-aligned hourly rate.
Next steps.
Send CV, a brief cover note and – if available – a few words on your own projects or repos to karriere@rte.de. We reply within 5 business days.
Typical flow: intro call (30 min) → short technical part (data/ML) → offer.
Apply now All open positionsWith SonicTC we made the jump from sampling to 100% inline testing – without replacing our existing hardware.
Questions about this role?
Drop us a short note at karriere@rte.de – also for theses and internships.