The postdoc will work as a researcher in a project on machine learning for time of flight cameras, and features collaboration between the Computer Vision Lab and the company Fotonic. 3D cameras using the time of flight (ToF) principle are increasingly popular for automation and robotics. Many new consumer products such as the Kinect v2, and the Microsoft Hololens device also rely on ToF for 3D mapping. We will together with Fotonic study the fundamentals of the measurement problem, and temporal fusion techniques, with the aim of improving depth map quality, range, and robustness.
The postdoc is expected to publish papers at high ranking venues such as ECCV, CVPR, ICCV and 3DV.
A Postdoc is appointed until further notice, but for no longer than two years. The appointment can be renewed if there are special reasons.
The University applies individual salary scales adapted to the experience of the employee and to the labour market.
The applicant should have a doctorate in computer vision or machine learning, or an equivalent degree from a foreign university. The doctorate shall have been obtained no longer than three years before the expiration date of the application.
Earlier publications in first class journals and highly-competitive conferences in areas relevant to the work is considered a merit. Applicants with a rigorous background in mathematics, signal processing, GPU programming, and machine learning will be prioritized. Prior experience with LIDAR or ToF cameras is beneficial.
Further details on the position can be provided on request by Associate Professor Per-Erik Forssen ([hidden email]) who is also the project manager, or by Professor Michael Felsberg ([hidden email]) who is heading the lab.