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 society of today, for example in the growing demands concerning efficient systems for communications and electrifying.
We offer a dynamic and international work environment with about 200 employees from more than 20 countries, and with 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
Information about the research group
The Computer Vision Group conducts research in the field of automatic image interpretation and perceptual scene understanding. 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 (particularly self-driving cars), image-based localization, structure-from-motion and object recognition. The main research problems include mathematical theory, algorithms and machine learning (deep learning) for inverse problems in artifical intelligence.
We are interested in improving the numerical optimization methods in computer vision and related fields. Numerical optimization is at the core of any computer vision and machine learning problem, and reaching a better numerical solution can make the difference between the desired answer and an unusable result.
One of the areas we are particular interested in is how to reach better local minima when minimizing highly non-convex objective functions. Improving the current state-of-the-art is beneficial for large-scale optimization problems in computer vision (such as bundle adjustment) and in machine learning (such as training a deep neural network). Two ways to reach better minima in practice are lifting (i.e. introducing a suitable over-parametrization of the original problem), and using surrogate objectives to “guide” around poor local minima. The aim of this project is also to explore how to combine numerical optimization and machine learning (“learning to optimize”).
Funding has been obtained from the Wallenberg AI, Autonomous Systems and Software Program (WASP) which is Sweden’s largest ever individual research program, a major national initiative for strategically basic research, education and faculty recruitment. The program is initiated and generously funded by the Knut and Alice Wallenberg Foundation (KAW) with 2.6 billion SEK. In addition to this, the program receives support from collaborating industry and from participating universities to form a total budget of 3.5 billion SEK. Major goals are more than 50 new professors and more than 300 new PhDs within AI, Autonomous Systems and Software. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. For more information about the research and other activities conducted within WASP please visit: http://wasp-sweden.org/
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.
Full-time temporary employment. The position is limited to a maximum of two years (1+1).
To qualify for the position of postdoc, you must have a doctoral degree in computer vision, machine learning, applied mathematics or a related 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.
Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.
Our offer to youChalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.
The application should be marked with Ref 20180721 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) including:
• 1-3 pages where you introduce yourself and present your qualifications.
• Previous research fields and main research results.
• Future goals and research focus. Are there any specific projects and research issues you are primarily interested in?
• 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: 15 January, 2019
For questions, please contact:
Research professor Christopher Zach
*** 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 eight Areas of Advance; Building Futures, Energy, Information & Communication Technology, Life Science, Materials Science, Nanoscience & Nanotechnology, 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!