Student Assistant (f/m/non-binary)

Supporting the Development of the Course Machine Learning in Civil Engineering

Contact

Name

Tom Schumann

Telephone

workPhone
+49 241 80-25228

E-Mail

Contact

Name

Arnd Pettirsch

Telephone

workPhone
+49 241 80-25224

E-Mail

Institution

Lehrstuhl und Institut für Straßenwesen

Our Profile

The Institute of Highway Engineering is proven and recognized as a research institution in the digitization of traffic and especially in application-oriented research. In order to transfer this research into teaching as well, a new course entitled Machine Learning in Civil Engineering will be created in the coming semesters.

Your Profile

  • Enrolled student in the field of computer science, computer science teaching, computer engineering, electrical engineering or a thematically related course of study
  • 3rd semester bachelor's degree or higher
  • Knowledge of programming with Python
  • Knowledge in the field of Machine Learning is advantageous
  • Independent and reliable way of working
  • Interest in topics of Machine Learning and teaching
  • English required
  • Intended minimum duration of the engagement: 1,5 year

Your Duties and Responsibilities

Your tasks in the conceptual design of the course including the creation of the teaching materials:

  • Conceptual support of the scientific staff in the creation of the curriculum
  • Support with the preparation of lecture and exercise materials
  • Working in a interesting research field and within a strong team

What We Offer

The successful candidate will be employed as a student assistant.
The position is to be filled at the earliest possible date and offered for a fixed term of three months.
A further employment is expressly desired.
This is a part-time contract position.
The standard weekly hours will be 8-12 hours.
The salary is based on the RWTH Guidelines for Student and Graduate Assistants.
The position corresponds to a pay grade of 11,80 € per hour.

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:V000003486
Application deadline:04/10/2022
Mailing Address:RWTH Aachen University
Chair for Highway Engineering at RWTH Aachen
Tom Schumann
Mies-van-der-Rohe Straße 1
52074 Aachen
Email:
Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail.