In manufacturing, a wide variety of use cases exist where Deep Learning (DL) and Machine Learning (ML) are successfully applied. Examples of use cases include the production of rockets, stem cells to fight blood cancer, optics, or lightweight components. In particular, tabular and image data are recorded during production. In the context of the thesis, DL - as well as ML pipelines are to be created for the applications of the production, which are taken in our industry projects directly on site into the operation. What you will do <ul> <li>Creation and preparation of image and tabular data in collaboration with experts</li> <li>Implementation of DL & ML models depending on the use case</li> <li>Comparison of DL-& ML-based methods with methods of classical data analysis</li> <li>Validation and documentation of results</li> </ul> What you bring to the table <ul> <li>You are studying mechanical engineering, computer science, industrial engineering or a comparable subject</li> <li>Experience in the field of machine learning is an advantage</li> <li>A high degree of initiative and team spirit</li> <li>Very good language skills in German and English</li> </ul> What you can expect <ul> <li>An excellent equipment of machines and devices</li> <li>Collaboration in industry or industry-oriented research projects and in a dedicated team</li> <li>Space for creative work</li> </ul> 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. 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! Questions according to this position will be answered by: Leo Hemmerich Research assistant »Production quality« Phone: +49 241 8904-584 Fraunhofer Institute for Production Technology IPT <a href="http://www.ipt.fraunhofer.de" target="_blank">www.ipt.fraunhofer.de</a> Requisition Number: 8382 Application Deadline:

BT/MT: »Deep learning and machine learning in production« (Aachen, DE, 52074) @ Fraunhofer-Gesellschaft

About this role

Ready to apply?