Research Associate (m/f/x) in the work field “Clean Traffic, especially Analysis of Vehicle Emissions”

TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country.
The "Friedrich List" Faculty of Transport and Traffic Sciences is the largest academic competence center in the field of transportation sciences in Germany and researches all modes of transport and mobility needs. At the Chair of Transport Ecology, we examine how climate‑friendly mobility and clean traffic can be understood today and in the future.
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.

Our working group has built a unique database that contains Europe‑wide remote emission sensing measurements from the past decades. You will continuously develop this database, integrate new field and laboratory measurements (remote sensing, plume chasing, PEMS, etc.) and evaluate them with advanced analytical and statistical methods. Multivariate analyses and machine learning approaches are particularly desired. You will cooperate with emission experts across Europe, be responsible for corresponding third‑party funded projects, and ideally lead the research group composed of several researchers.
Your expertise will be incorporated into teaching, especially through supervising lectures, seminars and student projects (according to HSDAVO). You will publish your results at international conferences and in peer‑reviewed journals. You will also take part in acquiring and managing further projects to expand the research field with the possibility of increasing your working hours.

• at least a good university degree in transportation or industrial engineering, environmental engineering, physics, data science, computer science or related fields
• proven experience in analyzing large datasets, e.g., with multivariate statistics or machine learning
• experience with relational databases, e.g., PostgreSQL
• knowledge of Linux, Git‑Bash and virtual machine configuration
• independence and initiative, combined with openness to discussion and feedback
• English and German language skills – one at C1 level, the other at least B1
  A relevant PhD, documented experience in project leadership and in obtaining external funding are advantageous.

• an exciting research and teaching position with development prospects
• flexible, family‑friendly work arrangements, including home‑office and mobile‑office options
• ergonomically equipped workstation with a notebook
• access to high performance computing resources
• professional and personal further training at TUD
• public service social benefits (health insurance, vacation, discounted job ticket, employee sports, corporate benefits)
• an international team with motivated colleagues in an open, committed atmosphere

TUD strives to employ more women in academia and research. We therefore expressly encourage women to apply. The university is a family-friendly university. 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 include in your application your motivation for the work and your ideas for developing the research group. Indicate which research questions you intend to address, which goals you aim to achieve within the first 24 months, and how you will approach the data analysis. Together with your curriculum vitae, list of publications, certificates, and an English summary of your master’s/diploma or PhD thesis (whichever is the most recent), please submit your application documents exclusively by e‑mail no later than October 14, 2026 (time stamp on the email server of TUD applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de as a single PDF file to jens.borken‑kleefeld@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.