Jobbeschreibung
Rosenheim Technical University of Applied Sciences is a regionally anchored university with an international reputation. It combines practical research with developing innovative new talents in the fields of technology, business, design, healthcare, and social sciences. The interdisciplinary cooperation between the faculties and institutes guarantees high quality results and outstanding teaching. Our values include sustainability, service orientation, and being family-friendly.
At the Campus Rosenheim, we are looking for a
Research Associate:
PhD Candidate / Postdoc (m/f/x)
This is a fixed-term position until August 31, 2027 (reference 2025-037-ZFET-Cy4MIE).
Are you fascinated by the transformative power of AI and eager to drive innovative research in cloud computing and IoT in the context of Industry 4.0? The rapid convergence of AI with industry is reshaping traditional processes and sparking entirely new business models. As research and education remain key to sustaining Germany's industrial competitiveness, we invite you to join our team. In this role, you will contribute to innovative R&D projects within the proto_lab ecosystem at TH Rosenheim, a platform dedicated to Industry 4.0 research, development, and technology transfer.
- excellent bachelor's or master's degree level in a technical field such as computer science or engineering
- a strong interest in applying machine learning techniques to technical systems, ideally complemented by initial experience in reinforcement learning
- proficient programming skills (ideally Python)
- practical experience in IoT, cloud, Unix, and/or embedded systems is an advantage
- ability to work independently as well as collaboratively within an interdisciplinary team
- excellent organizational skills coupled with a systematic approach to problem solving
- required language skills: level B2 in German
- participation in the EU project Cynnergy4MIE, where you scientifically explore the application of machine learning – specifically reinforcement learning for scheduling problems in the context of modern production environments
- development of new models and software for solving scheduling problems in the context of production on the basis of an existing in-house tool (mostly written in Python)
- preparation of scientific publications aimed at an international audience and engagement in our PhD program
- a demanding and independent position in an innovative and collegial environment
- a modern workplace with flexible working hours and a wide range of opportunities to combine family and work
- occupational health promotion
- remuneration according to pay category 13 of the collective agreement for the public service (TV-L) with all the special benefits customary in the public service