TU-ID: 120 | 2021 | 33 | 160882


University Assistant (Post-Doc)

40 hours/week | limited

TU Wien is Austria's largest institution of research and higher education in the fields of technology and natural sciences. With over 26,000 students and more than 4000 scientists, research, teaching and learning dedicated to the advancement of science and technology have been conducted here for more than 200 years, guided by the motto "Technology for People". As a driver of innovation, TU Wien fosters close collaboration with business and industry and contributes to the prosperity of society.
At the Department of Geodesy and Geoinformation, in the Research Unit of Geoinformation TU Wien is offering a position as university assistant (post-doc) until 31.08.2024 (maternity leave representation) for 40 hours/week. Expected start: March 2022.

We would like you to contribute to our research in the areas of Geographic Information Science and Spatial Artificial Intelligence. The areas we are interested in are: human navigation, human activity recognition, urban computing, spatial human-computer interaction, location based services and geospatial AI.


You will work together with a passionate and interdisciplinary team of researchers and model, analyze and interpret data collected through human subject experiments (location data, eye tracking and IMU data, etc.) as well as data from multiple other sources, e.g., OpenStreetMap. In your work, you will use artificial intelligence techniques and data from multiple sources. You will publish your results in international scientific journals and conferences. The laboratories of the group (https://geoinfo.geo.tuwien.ac.at/) will support your research and the exceptional IT infrastructure of the department (https://www.geo.tuwien.ac.at/) will be at your disposal.
  • Deep interest in scientific problems and the motivation for independent and goal-oriented research
  • Independent teaching or participation in teaching and supervision of students
  • The ability to develop methods, concepts, as well as their realization and evaluation and the willingness to contribute in interdisciplinary scientific projects
  • Participation in organizational and administrative tasks of the research division and the faculty

Your profile:

You have a doctoral degree in Computer Science, Geoinformation, Geomatics or similar. Furthermore, you are technically skilled and have programming experience, knowledge of statistics and machine learning. You have the ability to teach classes in GIScience with a heavy focus on implementation and algorithmic aspects of geographic information systems. You are creative, reliable and motivated with excellent oral and written communication skills in English, as well as proven experience in writing scientific papers. Knowledge in experimental design, the analysis of sensor data (e.g., eye tracking and IMU data), in project acquisition as well as communication skills in German, are advantageous. 
  • Completion of an appropriate doctorate and in-depth knowledge of the subject area
  • Experience in national and international research cooperation as well as in project management and presentations
  • Interdisciplinary work
  • Experience in teaching and publication activities as well as interest and pleasure in research and work/support with students
  • Organizational and analytical skills as well as a structured way of working
  • Excellent command of the English language and very good communicative skills and team competences

We offer:

TU Wien represents the largest Austrian University of Science and Technology conducting research, teaching and innovation under the motto 'Technology for people' for over 200 years. Over the years, TU Wien has evolved into an open academic institution built on strong foundations of basic and applied research as well as research-oriented teaching at the highest level. With its eight faculties (57 institutes and about 2.800 researchers) the TU Wien covers the whole value added chain within the classical engineering and natural science fields - basic as well as applied research projects provide newest findings and innovations.

Research at TU Wien is based on twin pillars: fundamental research at subject level together with the interdisciplinary integration, and application-orientated research built on this fundamental research. Together, they represent the key elements of the research output of TU Wien. With respect to the main role of university research, namely “generating knowledge to increase understanding and for the benefit of society”, these elements are directed towards utilizing this understanding and knowledge.
  • Continuing personal and professional education and flexible working hours
  • Central location of workplace with very good accessibility (U1/U2/U4 Karlsplatz)
  • A creative environment in one of the most liveable cities in the world
  • Additional benefits for employees can be found at the following link: Fringe-Benefit Catalogue of TU Wien
TU Wien is committed to increasing the proportion of women in particular in leadership positions. Female applicants are explicitly encouraged to apply. Preference will be given to women when equally qualified, unless reasons specific to a male applicant tilt the balance in his favour.

People with special needs are equally encouraged to apply. In case of any questions, please contact the confidant for disabled persons at the university, Mr. Gerhard Neustätter.
Entry level salary is determined by the pay grade B1 of the Austrian collective agreement for university staff. This is a minimum of currently EUR 3,945.90/month gross, 14 times/year for 40 hours/week. Relevant working experiences may increase the monthly income.

We look forward to receiving your application until 28.10.2021.
If you have any questions, please do not hesitate to contact us

Carmen Keck | T: +43 1 588 01 406201
Here you can find also relevant information about the application process.
Technology for People
Furthermore, please note that applicants will not normally be reimbursed for travel costs incurred in connection with this admission process.
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