Student Assistant (Reinforcement Learning for graph-based decision problems)

Fraunhofer-Gesellschaft, Germany

Updated: about 7 hours ago
Location: Wachtberg, NORDRHEIN WESTFALEN

In Fraunhofer FKIE, more than 500 employees develop technologies and processes with the aim of early detection, mitigation and management of existential risks. In close cooperation with strategic partners, the institute is dedicated to the entire processing chain of data and information: from acquisition, transmission and processing to reliable dissemination. The Fraunhofer FKIE offers enthusiastic developers challenging and varied tasks in a creative environment.

The department »Information Technology for Command & Control« (ITF) develops and tests architectures and interoperability solutions for complex information systems. Our research topics include the design of Command and Control Information Systems, AI-based services for intelligent user interfaces, information analysis and decision support systems, among others.

What you will do

You will work in a pleasant and exciting environment with an open, result-oriented, and cooperative atmosphere. You will have to opportunity to work on a both technically and operationally relevant, application-oriented topic. You will be supported by experienced colleagues. Constraints that come with your studies will be respected.

Within our experimental research framework for command & control decision support, you will have the opportunity to contribute to various tasks including:

  • Implementing or extending reinforcement learning algorithms.
  • Utilizing different types of graph neural networks to encode the states of graph-based decision problems.
  • Developing training pipelines, running experiments, and visually representing the results of trained models.

What you bring to the table

We are looking for a student of computer science or a related field with a focus on reinforcement learning. Programming knowledge is required. You have gained experiences with Python and the relevant packages for machine learning. Additional experience with libraries in reinforcement learning or, graph neural networks would be a plus. You are not afraid of learning new technologies and frameworks. You enjoy developing prototypes. You are independent, creative and curious and you can work independently.

What you can expect

  • Ideal conditions for practical experience alongside your studies.
  • The opportunity to complete a thesis with professional supervision.
  • Application-oriented topics at the interface between research and industry.
  • Mobile working is possible, however, taking into account one day of presence on site.

The weekly working time is by agreement, but maximum of 20 hours. The position is usually limited to 12 months. 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. 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. 

Interested? Apply online now. We look forward to getting to know you!

Dr. Hans-Christian Schmitz

Tel.: +49 228 9435-386

Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE 

www.fkie.fraunhofer.de  

Requisition Number: 74287                Application Deadline:


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