ABOUT US

RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket.
RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.
As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.
You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union’s General Data Protection Regulation (GDPR) at http://www.rwth-aachen.de/dsgvo-information-bewerbung.
Application
Number:
V000009228
Application deadline:
07/03/2025
Mailing Address:
RWTH Aachen University
Chair of Geotechnical Engineering and Institute of Geomechanics and Underground Technology
Tuna Sarac
Mies-van-der-Rohe-Str. 1
52074 Aachen
Email:
Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail

We’re seeking a motivated Student Assistant to contribute in the development of a new course titled “Physics-Informed Machine Learning Applied to Geotechnical Engineering”.

• Support in creating course materials, including coding examples, exercises, and potentially support in instructional content.
• Provide support to students by addressing their inquiries and explaining course concepts.
• Assist with ongoing projects, mainly focused on using neural networks to simulate complex problems in soil mechanics and soil dynamics.