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).

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
Learn more and apply here: https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pages/default.aspx?rmpage=job&rmjob=9721


Application deadline: 31 August, 2021