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FRFraunhofer-Gesellschaft

Student assistant: Physics-based Machine Learning for Process Optimization in Machining Domain(m/w/x)

Aachen
Part-timeWorking StudentOn-site
AI/ML
Data Science

Development of ML algorithms for dynamic phenomena in milling processes at research organization with 76 institutes. Solid Python or C++ programming skills required. Flexible working hours, access to state-of-the-art machine park.

Requirements

  • Studies in Mechanical Engineering, Computer Science, Mechatronics or comparable subject
  • Solid background in programming (Python or C++)
  • Experience with machining processes or ML approaches (advantageous)
  • High degree of motivation, initiative, and independence
  • Good language skills in German and/or English

Tasks

  • Develop machine learning algorithms for milling processes
  • Implement algorithms to model dynamic phenomena
  • Analyze dynamic phenomena in milling processes
  • Explore Physics-Informed and Physics-Guided Machine Learning
  • Apply Physics-Informed and Physics-Guided Machine Learning
  • Design cloud-based microservices for industrial manufacturing
  • Develop cloud-based microservices for industrial manufacturing

Education

Currently in higher education

Languages

GermanBusiness FluentEnglishBusiness Fluent

Tools & Technologies

PythonC++ML approaches

Benefits

Flexible Working

  • Flexible working

Diverse Work

  • Innovative research projects
  • Diverse and adaptable tasks

Other Benefits

  • Practical knowledge implementation
  • Edge cloud systems
  • Practice-oriented thesis opportunity

Modern Equipment

  • State-of-the-art machine park
  • 5G infrastructure
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