Postdoc in artificial intelligence for naturalistic driving analysis

Information about the research
This interdisciplinary pos-doc position joins three research groups at three different department within Chalmers: the Crash Analysis and Prevention Unit at the Department of Mechanics and Maritime Sciences, the Data Science and Artificial Intelligence (AI) Division at Department of Computer Science, and Engineering and the Computer Vision Group at the Department of Electrical Engineering Department.*

The researchers in the Crash Analysis and Prevention (CAP) unit within the Vehicle Safety division (Department of Mechanics and Maritime Sciences) at Chalmers University of Technology conduct world-leading research on topics related to traffic safety. The mission of the unit is to understand why crashes happen and how they can be prevented. This includes understanding crash causation mechanisms related to the road-user (e.g., driver) behaviour as well as (e.g., automated) vehicle and environment factors.

The Data Science and AI, division is a relatively new division in the Department of Computer Science and Engineering, reflecting how this area has grown considerably over the last years, recruiting new PhD students, post-docs, and faculty members. The main research areas of the division are algorithms, machine learning, AI, and different applications of data science. The division has a solid network of collaborators, both academic and industrial, within and outside of Gothenburg, the home of Chalmers.

The Computer Vision Group at the Department of Electrical Engineering conducts research in computer vision applications such as autonomously guided vehicles (particularly self-driving cars), image-based localization, structure-from-motion and object recognition. The main research problems include mathematical theory, algorithms and machine learning (deep learning) for inverse problems in artificial intelligence. 

Major responsibilities
The successful applicant will apply machine learning and other AI methods to large datasets of naturalistic data to solve traffic safety issues, typically related to human factors in automation. The post-doc will have the unique opportunity to work in three different research groups at three different departments within Chalmers to carry over this interdisciplinary project where behavioral science, machine learning, and video analysis come together to improve transport. This post-doc will develop and apply artificial intelligence algorithms to large naturalistic datasets in order to analyze and model how driver behave in traffic in safety-critical and non-safety-critical situations. Large part of the work will include the extraction and analysis of human behavior from video including, as an example, posture, glance behavior, and secondary tasks to driving.

This project will synergize with other projects ongoing at SAFER, the Vehicle and Traffic Safety Center at Chalmers. An example is the European project L3Pilot (www.l3piolot.eu), another example is the project FOT-e that is under consideration for financing from VINNOVA within the FFI framework.

The main aim of this post-doc project is to leverage on large naturalistic datasets available at SAFER and new data, that will be collected in L3pilot from automated vehicles, to develop and apply artificial intelligence methods that can support traffic safety research. This project will improve video coding, a process that today is still performed manually and severely hinder our ability to exploit large datasets of naturalistic data.

This position is jointly sponsored by CHAIR (Chalmers AI Research Center) and the Area of Advance Transport, therefore the post-doc will contribute to CHAIR initiatives (organization of research seminars and short courses or the supervision of master theses) for 10% of her time.

Your major responsibility as postdoc is to perform your own research in a research group. The position also includes teaching on undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. 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.

Position summary
Full-time temporary employment. The position is limited to a maximum of two years (1+1).

Qualifications
To qualify for the position(s) as PostDoc, you must have been awarded a doctoral degree in computer science or engineering, preferably within the last three years from the time of employment. The position requires fluent verbal and written communication skills in English. If Swedish is not your native language, Chalmers offers Swedish courses. Proficiency in programming is required.

Experience from publishing articles in international scientific journals is also a must, as well as documented experience of presenting research results in front of a large audience. Education and/or experience from the following areas will be considered advantageous: artificial intelligence, active safety, driver modelling, human behaviour analysis, video analysis. 

About the application procedure


*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***