FIR e. V. an der RWTH Aachen
Master's thesis: Adaptation of MLOps for the integration of AI/ML in maintenance
TLDR
Tailor MLOps approaches to integrate AI/ML in maintenance, delivering a practical, implementable pipeline framework and action-oriented recommendations.
Your tasks:
- Literature and market research on current trends and technologies in the field of MLOps and their application in maintenance
- Analysis of specific maintenance requirements for AI/ML models and their operation
- Development of an adapted MLOps approach that facilitates the integration of AI/ML in maintenance
- Derivation of recommendations for action and creation of practice-oriented documentation
Your profile:
- You are studying industrial engineering, mechanical engineering, computer science or similar
- You have very good written and spoken English skills
- You are characterized by an independent and committed as well as careful and goal-oriented way of working
- You are confident in using the common MS Office programs
Our offer:
- Insights into the industrial and research business in collaboration with well-known companies and research partners
- Interesting, challenging and varied tasks in a qualified and dynamic team
- The opportunity for flexible time management and independent work
- A modern, collegial and digital working environment
- Room for creativity and your personal development
Benefits
Flexible Work Hours
The opportunity for flexible time management and independent work
Remote-Friendly
A modern, collegial and digital working environment
FIR e. V. at RWTH Aachen is dedicated to guiding companies through their digital transformation towards Industry 4.0. We develop methodologies and tools that help businesses adopt digital business models and optimize their processes using the latest technologies in a complex, value-driven landscape.