Student assistant: Physics-based Machine Learning for Process Optimization in Machining Domain
Role details
Job location
Tech stack
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 & conditions
- 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
We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable - for applicants with disabilities, we work together to find solutions that best promote their abilities. Remuneration according to the general works agreement for employing assistant staff.
With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.