Internship in Reinforcement Learning Based Planning and Control of Modular Production Systems Starting October 2023

Stellenbezeichnung: Internship in Reinforcement Learning Based Planning and Control of Modular Production Systems Starting October 2023

Firma: Mercedes-Benz

Arbeitsort / Location: Sindelfingen, Baden-Württemberg

Job Beschreibung: Life is always about becoming… Becoming means going on a journey to be the best version of our future selves. While we discover new things, we will face challenges, master them and grow beyond our individual limits. Apply for a job at Mercedes-Benz and find your individual role and workspace to unleash your talents to the fullest. Empowered by visionary colleagues who share the same pioneering spirit. Joining us means becoming part of a global team that aims to build the most desirable cars in the world. Together for excellence.

Job-ID: MER0002QD9_EN

The team Digital Twin produces new software solutions for the factory of the future. The objective of the Digital Twin is to develop software modules that assist and optimize the planning, realization and control of all relevant planning processes of highly automated production systems.

The surge of electric vehicles increases the diversity in the body-in-white production drastically. Conventional assembly lines struggle to meet the adaptability requirements imposed by this development. Therefore, our team is conducting research on new, modular production systems, which meet the flexibility requirements, and the interplay between production and logistics. In your internship, you will participate in this domain of research.

We have a simulation-based reinforcement learning approach to optimize the material flow through the modular production system. In your internship, you will expand this approach and use state of the art methods from literature to improve the learning behaviour of the reinforcement agent.

These challenges await you:

  • Literature research
  • Further development and optimization of the reinforcement learning approach
  • Optimisation of the learning behaviour of the reinforcement learning agent
  • Validation of the approach in different use cases

The starting date is flexible. Please state your preferred starting date in your application.

  • Field of study: computer science or similar field of study with very good grades
  • Very good Python skills
  • Extensive practical experience with Tensorflow or Pytorch
  • Ideally you have experience with reinforcement learning
  • Very good communication skills and proficiency in English or German
  • Ability to work in a team
  • Analytical way of thinking and strategic way of working

Additional information:

It doesn’t work completely without formalities. When sending your online application, please attach your CV, certificate of enrollment, current performance record, relevant certificates, if applicable proof of mandatory internship and the standard period of study (max. 5 MB) and mark your application documents as „relevant for this application“ in the online form.

Please find the criteria of employment https://group.mercedes-benz.com/karriere/studenten/“>here.

Citizens of countries outside the European Trade Union please send, if applicable, your residence / work permit.

We particularly welcome online applications from candidates with disabilities or similar impairments in direct response to this job advertisement. If you have any questions, you can contact the local disability officer once you have submitted your application form, who will gladly assist you in the onward application process: SBV-Sindelfingen@mercedes-benz.com

Please understand that we no longer accept paper applications and that there is no right to get your documents returned.

If you have any questions regarding the application process, please contact HR Services by e-mail at hrservices@mercedes-benz.com or the https://group.mercedes-benz.com/karriere/studenten/“>Chat-Bot on our career page via the plus symbol.

Mr Gelfgren will happily answer questions about the position.

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