Postdoc in Model based deep learning

We have a broad interest in developing strategies to incorporate various types of prior knowledge into deep learning models and training procedures. This entails different physics-based models, probabilistic models and invariances. The advantages and potentials include better scalability and performance for iterative optimization methods, compensation for model inexactness, improvements in generalization capabilities outside a training dataset, and reduction in training effort (smaller dataset size, fewer parameters).

Information about the research project
This is an open-ended research project allowing a talented researcher the freedom to define his or her own research project in collaboration with one or more of the senior researchers in the signal processing group. The purpose of this project is to investigate and develop novel model-based deep machine learning methods for automatically interpreting and making sense of signals coming from sensors such as cameras, radars, lidar, medical imaging, etc. and solving interesting and challenging problems with applications to a wide variety of fields. Examples of possible research directions, where the deep learning procedures can leverage on models or invariances, could be:

• Teaching a self-driving vehicle to localize itself by continuously learning what good visual features/landmarks are and how we can robustly describe them.
• Model-based deep learning for non-homogeneous clutter mitigation in radar systems or low complexity signal detection in dense radar scenarios using approximation learning.
• Deep probabilistic models for semi-supervised learning with noisy labels.
• Physics-informed neural networks for forward and inverse problems in sensor systems.

Information about the research group
The Signal Processing group conducts research in the field of physical and statistical signal and image modelling, statistical inference and machine learning. We actively pursue research in target tracking, array signal processing, estimation, detection and machine learning. Projects range from the development of mathematical theory, method development and applications in the area of perception for autonomous vehicles, land and airborne radar systems.

Information about the department
At the Department of Electrical Engineering, research and education are performed in the areas of Communication and Antenna systems, Systems and Control, Computer Vision, Signal Processing and Biomedical Engineering, and Electric Power Engineering. Our knowledge is of use everywhere where there is advanced technology with integrated electronics. We work with challenges for a sustainable future in the society of today, for example in the growing demands concerning efficient systems for sensing, communications and electrification.

We offer a dynamic and international work environment with about 220 employees from more than 20 countries and extensive national and international research collaborations with academia, industry, and society.

The department provides about 100 courses, of which most are included in the Master’s Programs ”Biomedical Engineering”, “Electric Power Engineering”, ”Systems, Control and Mechatronics” and ”Communication Engineering”.

Read more at www.chalmers.se/en/departments/e2

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.

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

Qualifications
The candidate should have a strong background in machine learning, with a focus on (deep) machine learning for signal processing or computer vision.

The candidate should have published at least one paper in an IEEE journal related to the topic, or 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 have demonstrated potential for research, research communication and teaching. If you obtained your PhD degree from Chalmers you must have worked as a researcher 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.

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
The application should be marked with Ref 20210360 and written in English. The application should be sent electronically and be attached as pdf-files, as below:

CV:(Please name the document as: CV, Surname, Ref. number) including:
• CV, include complete list of publications
• Previous teaching and pedagogical experiences
• Two references that we can contact.

Personal letter: (Please name the document as: Personal letter, Family name, Ref. number)
1-3 pages where you:
• Introduce yourself
• Describe your previous research fields and main research results
• Describe your future goals and future research focus

Other documents:
• Attested copies of completed education, grades and other certificates.

Please use the button at the foot of the page to reach the application form. The files may be compressed (zipped).

Application deadline: 31 August, 2021

For questions, please contact:

Prof. Tomas McKelvey,
Signal Processing and Biomedical Engineering,
[email protected] ,
+46 31 772 8061

Prof. Lennart Svensson,
Signal Processing and Biomedical Engineering,
[email protected] ,
+46 31 772 1777

Asoc. Prof Lars Hammarstrand,
Signal Processing and Biomedical Engineering,
[email protected] ,
+46 31 772 1788

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

Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our six Areas of Advance; Energy, Health Engineering, Information and Communication Technology, Materials Science, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!    

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