瑞典查尔姆斯理工大学计算机视觉方向博士后职位

At the Department of Signals and Systems, we conduct internationally renowned research in biomedical engineering, antenna systems, signal processing, image analysis, automatic control, automation, mechatronics, and communication systems. We offer a dynamic and international research environment with about 150 employees from more than 20 countries, and with extensive national and international research collaborations with academia, industry and society. The department provides more than 70 courses, of which most are included in the Master’s Programs ”Biomedical Engineering”, ”Systems, Control and Mechatronics”, and ”Communication Engineering”.

Information about the research group and the project
The Computer Vision Group conducts research in the field of automatic image interpretation. The group targets both medical applications, such as the development of new and more effective methods and systems for analysis, support and diagnostics, as well as general computer vision applications including autonomously guided vehicles, image-based localization, stereo and structure-from-motion. The main research problems include mathematical theory, algorithms and machine learning for inverse problems such as reconstruction, segmentation and registration.

The goal of this project is to further the use of modern optimization methods in computer vision and related areas including image analysis, pattern recognition and robotics. The priority of the project is centered on the development of novel and theoretically justified algorithms relevant to basic key problems in practical applications such as image localization, registration, stereo and autonomous navigation, or ultimately, relevant to visual scene understanding.

There are two major issues that make application problems in vision particularly challenging which will be addressed. The first one is related to robustness and the ability to handle outliers. The problem of fitting a mathematical model to data is a well-studied subject, though standard techniques, for example, least-squares regression do not apply. This is because real-life images are almost always contaminated by noise including measurement noise and outliers, i.e., data that do not belong to any coherent structure. We aim at developing new computational methods for robust model estimation with guaranteed performance as well as assessing the intrinsic computational complexity of such problems. The second issue concerns regularization and incorporation of prior information into the model. We will investigate several new techniques in order to handle more complex models including geometric shape regularization.

Major responsibilities
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 of postdoc, you must have a doctoral degree in a relevant field (physics, mathematics or computer science); the degree should generally not be older than three years. You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education.

The position requires sound verbal and written communication skills in Swedish and English. Chalmers offers Swedish courses.