Assistant Professor in Intelligent Transport Systems

Information about the research group
The signal-processing group has a strong background in model-based signal processing using, among other things, tools from mathematical statistics and numerical methods. Our “classical” applications are found in wireless communications and radar signal processing, where we work with channel estimation, adaptive antennas and high-resolution methods.

We are nowadays spreading the technology to other areas, where modern signal processing can advance the state of the art, for example through refined interpretation of measurements. Examples of such projects include:
• microwave sensor systems
• automotive signal processing (engine control and intelligent transportation systems)
• video and image analysis
• analysis of EEG and other biomedical signals.

The mixture of basic research in statistical signal processing and new application areas has been fruitful and we plan to continue in the same spirit.

Major responsibilities
Your primary duty as non-tenured assistant professor is to perform your own research, generally as a member of a research group. The position also includes teaching for about 20 per cent of your working hours, primarily at undergraduate and master's levels. Supervising PhD students to a certain extent is also included. Another important aspect involves collaboration within academia and with society at large. The position is meritorious for future research duties within academia as well as industry/the public sector.

The main focus of the research should be on automotive ITS and especially, but not exclusively, the perception subsystem of autonomous vehicles. The goal is to support the development of an autonomous vehicle research platform in the form of an actual vehicle equipped with sensors and processing units. The developed perception subsystem should solve the following problems:
• Positioning of the host vehicle (globally, relative to a map and relative to other road users),
• Models to represent the current traffic situation around the host vehicle (roads, infrastructure, vehicles, VRUs, etc.),
• Fusion algorithms to estimate the parameters in the aforementioned models using noisy sensor observations as well as vehicle-to-vehicle communication.

The research will be conducted in a team consisting of PhD students and fellow senior researchers. The responsibilities of the Assistant Professor include to lead the running activities of the team and to co-supervise PhD students.

Position summary
Full-time temporary employment for a maximum of four years. Progress will be assessed after two years. You are expected to achieve associate professor expertise within four years. Assistant Professor is a position that offers an opportunity to qualify for higher research positions, both in academia and in society at large.

Qualifications
To qualify for the position of non-tenured assistant professor, you must have a doctoral degree in signal processing or a relevant field; the degree should generally not be older than five years. You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. Experience from a postdoc position or qualified research and development in industry/the public sector is meritorious.

Other meritorious experiences and skills are:
• Experience in leading/developing a sensor fusion platform for in-vehicle implementation.
• Access to a well-developed professional network within the automotive industry as well as researchers in the field.

In addition, a theoretical background in the following areas is desired:
• Bayesian filtering and estimation
• Statistical modelling
• Mapping
• Optimization

The position requires sound verbal and written communication skills in Swedish and English. If Swedish is not your native language, you should be able to teach in Swedish on undergraduate level after two years.

Application deadline: 2014-03-31

For questions, please contact:
Professor Tomas McKelvey, Signal processing and Biomedical engineering, mckelvey@chalmers.se, +46 31-772 80 61
Associate Professor Lennart Svensson, Signal processing and Biomedical engineering, lennart.svensson@chalmers.se, +46 31-772 17 77
Professor Arne Svensson, Head of the S2 Department: arne.svensson@chalmers.se, +46 31-772 17 51  


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