The Aschaffenburg University of Applied Sciences (TH AB) is an ambitious and family-friendly university in Germany, Rhine-Main area, which is characterized by business-related, predominantly inter-disciplinary, and innovative courses. It conducts practice- and application-oriented research in a wide variety of areas of technology and economy within numerous collaborations, as well as in the univer-sity's own institutes and laboratories.
TH-AB with its research team on “Connected Urban Mobility – Intelligent Traffic Infrastructure” is one of the partners of the consortium behind the project i4Driving, funded (10/2022-10/2025) by the EU Horizon Europe research and innovation programme. The objective is to deliver a library of credible models of heterogeneous human driving behaviors as a road safety baseline for CCAM virtual assessment.
The following position is to be filled at the Aschaffenburg University of Applied Sciences as soon as possible:
Research Assosiate/PostDoc/PhD Graduate Student (m/f/d)
This position is with a weekly working time of 40,10 hours, limited to 30/09/2025.
Application reference number pr-w-373
What are your main tasks?
- Applied Research & Development of artificial intelligence (AI) methods for innovative concepts of Cooperative Connected Autonomous Mobility (CCAM) in order to develop a set of building blocks that support the: "Design of the Self-Driving License for Autonomous Vehicles" towards a trustworthy driving style, like a skilled human driver, while being safer, comfortable and more energy/traffic efficient
- Use of AI-methods to evaluate traffic data and for the extraction of causality relations between data features from Naturalistic Driving Studies (NDS) and Driving Simulation Experiments (DSE), initially including a small number of critical events
- Simulation of critical traffic conditions, generation of use-cases and simulation scenarios to continuously challenge human drivers and to generate data for mining and testing
- Data Mining of causal relations and new patterns between external and human factors, and safety-critical driver behaviors for driving situations at intersections, in city- and in highway-traffic
- Transfer knowledge of cognitive modelling and decision making in systems under uncertainty, to recognize the intentions and behaviors of Connected Cooperative Automated Vehicles and of surrounding traffic participants
- Augment models with a 4D perception-cognitive layer for monitoring and root cause analysis, based on the data analysis with sensor measurements (from both real traffic and test field, incl. open Source Data) and simulated critical traffic conditions, including disturbances (e.g. congestions)
- Modeling the diversity of heterogeneous human driver behaviors and the complexity of the road traffic system into simulation, including a variety of “uncritical-”, safety critical- and specific driving situations in daily traffic
- Encode heterogeneous human driving behaviors into probabilistic human behavioral models
- Develop robust AI methods for situation analysis and explanations of decisions/conclusions to use for prevention
- Model Validation (traffic and safety robustness; resilience of requirements of the Autonomous Driving Systems)
- Model Verification (i.e. software meets specifications)
What are our expectations?
- Knowledge and/or willingness to learn new methods of artificial intelligence
- Well-founded knowledge of probabilistic and mathematical model building, cognitive modelling, probabilistic graphical models, decision support, simulation, and development environments
- Knowledge of data processing and statistical tools to explore and analyze data
- Confident work with simulation and development software MATLAB / SIMULINK for multi-sensor applications
- Experience with traffic simulation environments for traffic flow analysis, situation analysis and safety
What are our employment requirements?
- Successfully completed university degree (Master of Science or Master of Engineering) in one of the study fields: information technology, computer/data science, cybernetics, physics, mathematics, mechatronics, electrical engineering, or a related subject
Holders of a foreign university degree will be asked to present a Statement of Comparability issued by the Central Office for Foreign Education (“Zentralstelle für ausländisches Bildungswesen”) before signing the contract. We recommend to apply early (https://www.kmk.org/zab/statement-of-comparability.html) to avoid delays.
- Programming experience in python/spark and/or C/C++
What do we offer?
- An interesting work environment with a wide opportunity for self-influence on the own work
- The opportunity to gain a PhD or to collaborate as a Postdoctoral researcher with international experts
The employment relationship and remuneration are based on the provisions of the collective agreement for the civil service of the German federal states (TV-L), EG 13
The Aschaffenburg University of Applied Sciences welcomes women who feel addressed by the advertisement. Severely handicapped persons (please enclose a copy of the severely handicapped ID card with your application documents) will be given preference if their suitability, ability and professional performance are otherwise comparable.
IInterested? Please apply with your detailed application documents by October 21th, 2022 via our online portal at https://stelle.io/uzkua. If you have any questions, please do not hesitate to contact Prof. Dr. Galia Weidl, Tel. +49 - 6021 / 4206-326.
You can find information on data protection at: https://www.th-ab.de/hochschule/die-th-aschaffenburg/arbeiten-an-der-th-ab/stellenangebote
Technische Hochschule Aschaffenburg
University of Applied Sciences Aschaffenburg
Würzburger Str. 45