Fraunhofer-Gesellschaft

Student Assistant – Physics-based Machine Learning, Process Optimization, Machining

Fraunhofer-Gesellschaft

internship

Posted on:

Location Type: Office

Location: Aachen • Germany

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Job Level

Entry Level

Tech Stack

CloudMicroservicesPython

About the role

  • Develop and implement machine learning algorithms to model and analyze dynamic phenomena in milling processes
  • Explore and apply Physics-Informed / Physics-Guided Machine Learning approaches
  • Design and develop cloud-based microservices for industrial manufacturing applications

Requirements

  • You are studying Mechanical Engineering, Computer Science, Mechatronics or a comparable subject
  • Solid background in programming (e.g., Python or C++) is essential
  • Experience with machining processes or ML approaches are advantageous
  • A high degree of motivation, initiative, independence
  • Good language skills in German and/or English
Benefits
  • Collaboration in innovative research projects and the chance to implement your knowledge from your studies in practice
  • A state-of-the-art machine park equipped with edge cloud systems and 5G infrastructure
  • Flexible working to combine studies and job in the best possible way
  • The opportunity to write your practice-oriented thesis with us
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningPythonC++cloud-based microservicesPhysics-Informed Machine LearningPhysics-Guided Machine Learningprogrammingdata analysisalgorithm developmentindustrial manufacturing
Soft Skills
motivationinitiativeindependencecommunicationlanguage skills