Postdoc position in Signal Processing/Machine learning
Chalmers Tekniska Högskola AB / Högskolejobb / Göteborg
2023-08-08
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Project description
Autonomous cars need to localize themselves reliably in the road network in order to be able to plan ahead and safely follow planned paths. Localization is typically performed via a pre-built map, where the car establishes correspondences between data captured by its sensors, such as cameras, lidars and radars, and the map. These correspondences are then used to estimate the position and orientation of the car with respect to the map.
One key challenge for localization approaches, which is highly relevant to autonomous vehicles, is long-term operation. As the appearance and geometry of the scene change over time, it becomes harder and harder to detect the same landmarks in our current sensor data that we describe in our map and correctly associate them to each other. Examples for such changes include illumination changes over the course of a day or seasonal changes that affect the vegetation. However, current state-of-the-art approaches for keypoint detection and description are only moderately robust to such changes.
This project aims to tackle the long-term operation problem through continuous map updates and keypoint detector and descriptor learning. The map update step will provide training data for the detector and descriptor learning stage. Improved local features will in turn lead to better maps and more accurate localization results. To facilitate this research, we have a large image dataset with ground truth poses collected over a whole year as well as the ability to collected our own georeferenced data using Chalmers' ReVeRe-lab. Applicants are also encouraged and provided freedom to pursue their own research ideas, both within the context of the project as well as through collaborations outside of it.
Information about the research groups
The Signal Processing group at the department of Electrical Engineering conducts research in the field of physical and statistical signal and image modeling and inference. We actively pursue research in target tracking, array signal processing, estimation, detection and machine learning. Projects range from development of mathematical theory, method development and applications in the area of perception for autonomous vehicles, radar systems and biomedical devices.
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.
Chalmers AI Research Centre (CHAIR)
This project is funded by the Chalmers AI Research Centre (CHAIR). CHAIR aims at increasing Chalmers' expertise and excellence in Artificial Intelligence. Its objective is to conduct world-leading research for the benefit of both industry and the public sector. CHAIR's focus is on developing unique AI expertise in research, education, and innovation, and offering a highly attractive environment for world-leading AI researchers. The goal is to become the preferred AI partner for Swedish industry.
Major responsibilities
The major responsibility is to perform your own research in a research group and lead the efforts on the above mentioned research project. The position may also include teaching on master's level 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.
Qualifications
The candidate should have a strong background in machine learning, with a focus of (deep) machine learning for computer vision. Experience in learning novel keypoint detectors or descriptors is preferred. An additional background in 3D computer vision, especially Structure-from-Motion, SLAM, or visual localization, is desirable, but not necessary.
The candidate should have published at least one paper in one of the main international conferences in the fields of computer vision (ICCV, ECCV, CVPR), robotics (ICRA, IROS) or machine learning (NeurIPS, ICML, ICLR).
To qualify for the position of postdoc, you must have a doctoral degree in a relevant field; 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. If you obtained your PhD degree from Chalmers you must have worked as a reasearcher somewhere else for at least one year after obtaining your PhD.
The position requires sound verbal and written communication skills in English. If Swedish is not your native language, Chalmers offers Swedish courses.
Contract terms
This postdoc position is a full-time temporary employment for three years.
We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.
Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.
Application procedure
To apply, please go to:
https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=11981Application deadline: 1 September, 2023
Ersättning enligt kollektivavtal
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Arbetsgivare Chalmers Tekniska Högskola AB (org.nr 556479-5598)
Jobbnummer 8014070
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