• Teaching, including independent realisation of exercises and seminars in the areas
  of machine learning, deep learning, software development
• Research in the field of data-based modelling of non-linear structural dynamics and friction
  physics
• Method development of physics-integrating learning processes
• Implementation of scientific open-source programme code with high quality standards
• Publication of scientific results in international journals and at specialist conferences

• A successfully completed scientific university degree (Master, Diplom or equivalent) in Engineering Sciences, Physics, Applied Mathematics or Computer science
• Proven experience in university teaching
• Sound knowledge of mechanics and nonlinear dynamics
• In-depth knowledge of machine learning and deep learning with proven programming experience in Python, Keras, PyTorch
• Sufficient language proficiency to teach classes in German and English is expected; willingness to learn missing language skills is required
• Skills in scientific publishing and presenting is desired
• Curiosity, ability to work independently, communication skills, ability to work in a team, intercultural competences is a plus

• An inclusive and appreciative working atmosphere in a committed and diverse team
• The compatibility of family and career through flexible working time models incl. home office

Please send your application with the reference number and the usual documents only via email (bundled in one PDF document; max. 5 MB) to Prof. Dr.-Ing. Merten Stender via administration@cpsme.tu-berlin.de.

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.