Technische Universität Dresden - Chair of Big Data Analytics in Transportation
TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. For TUD diversity is an essential feature and a quality criterion of an excellent university. Accordingly, we welcome all applicants who would like to commit themselves, their achievements and productivity to the success of the whole institution.
Research Assistant (m/f/x) - 9 hrs./week
At the „Friedrich List“ Faculty of Transport and Traffic Sciences, Institute of Transport and Economics, the Chair of Big Data Analytics in Transportation is seeking to employ an academic as Research Assistant (m/f/x) (9 hrs./week) starting November 1, 2026. Due to funding constraints, the vacancy is initially limited until March 31, 2027. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG) as well as the Higher Education Act in the Free State of Saxony (Sächsisches Hochschulgesetz – SächsHSG) in conjunction with the TdL guidelines (collective bargaining association for the German federal states) for Student Assistants and Research Assistants dated February 28, 2024.
The Chair of Big Data Analytics in Transportation at the “Friedrich List” Faculty of Transport and Traffic Sciences at TU Dresden focuses on statistical methods and machine learning techniques for processing, analyzing, and modeling complex, often multidimensional data from the fields of mobility, transportation, and economics.
Tasks:
As a tutor, you'll support us in English taught courses on data analytics and machine learning.
Requirements:
- student enrolled at a German university with a college degree (e.g., a bachelor’s degree), for example (but not exclusively) in one of the following fields: transportation sciences, (geo)informatics, data science, mathematics, or economics
- practical experience with the data analytics programming language R
- ability to work independently and reliably
How to apply:
We welcome applications from candidates with disabilities. If multiple candidates prove to be equally qualified, those with disabilities or with equivalent status pursuant to the German Social Code IX (SGB IX) will receive priority for employment.
Application: Please submit your detailed application with the usual documents by September 25, 2026 (stamped arrival date of the university central mail service applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de exclusively by sending it as a single pdf file to pascal.kerschke@tu-dresden.de. Expenses incurred in attending interviews cannot be reimbursed.
TUD is a founding partner in the DRESDEN-concept alliance.
Reference to data protection: Your data protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis
Facts
ID: 206923
- Num. of employees:
- 8000
- Site:
-
- Dresden (Saxony, Germany)
- Type:
- Academic assistant
- Duration:
- initially limited until March 31, 2027
- Part-/Full-time:
- 9 hrs./week
- Starting date (earliest):
- At the earliest possible
- Remuneration:
- Remuneration rate WHK
- Scope:
- Natural sciences
- academia and research
- teaching (university)
- data science
- Field of studies:
- Natural sciences and mathematics
- business management
- geosciences
- mathematics
- transport
- Working language and expected level:
-
- German (Fluent in speech and writing)
Actions
Apply
- Closing date:
- 25/09/26
- Reference number:
- 38_W_2026
- By email:
- pascal.kerschke@tu-dresden.de
- Application papers:
- with the usual documents