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

WE OFFER

• 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
  The Rosenheim Technical University of Applied Sciences is committed to promoting professional equality between women and men, regardless of their origin, skin colour, religion, age, and sexual identity. Severely disabled applicants are given preferential treatment if they are otherwise essentially of the same suitability, competence, and professional performance.
  As we want to increase the proportion of women in technical fields, we are particularly looking forward to receiving applications from qualified women.
  For foreign university degrees, a certificate evaluation from the Central Office for Foreign Education (ZAB) must be submitted during the hiring process for the final assessment of the employment requirements.
  Please apply exclusively online via our applicant management system (application deadline: April 6, 2025).
  If you have any technical questions, please contact Prof. Dr.-Ing. Noah Klarmann,
  e-mail: noah.klarmann@th-rosenheim.de, phone: +49 8031 805-2661.
  www.th-rosenheim.de
  Technische Hochschule Rosenheim, Hochschulstrasse 1, 83024 Rosenheim, 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