Parts Interpreter responsible for sourcing and supplying automotive parts and accessories at Grand Toyota Clarkson. Role includes managing stock levels, processing orders, and providing service to customers.
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Onsite Architecture for Anomaly Localization: Concept and Implementation
Posted last week
About the role
- Developing a modular system architecture for anomaly localization in compressed air systems using Physics-Informed Neural Networks at Fraunhofer Institute. Focus on energy efficiency and sustainability in industrial applications.
Responsibilities
- Design, implementation, and evaluation of a modular system architecture for anomaly localization in compressed air systems based on Physics-Informed Neural Networks (PINNs)
- Structure sensor data acquisition, preprocessing, and modeling in a clear and reproducible way
- Explicitly incorporate physical system knowledge
- Integrate multiple modeling approaches (baseline and PINN-based methods)
- Enable robust and generalizable localization of anomalies
Requirements
- Enrolled at a German university or university of applied sciences (Fachhochschule)
- Strong analytical skills
- Programming experience in Python
- Interest in data-driven and physics-based methods
- Independent and structured working style
- Ability to design, implement, and evaluate innovative architecture and modeling approaches
Benefits
- Work in the exciting and innovative field of energy data analysis
- Pleasant working atmosphere within a motivated team
- Flexible working hours (e.g., to accommodate exam preparation)
- Home office available by arrangement
- If desired: close supervision with weekly coordination meetings
- Opportunity to contribute to publications
- Apply theoretical knowledge from your studies in practice and gain experience with the challenges of working with real-world data
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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