PhD Student Position in Deep Learning and Optimization

Chalmers University of Technology



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 electrification. 

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”.


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.

Information About The Project
We are interested in optimization methods for deep learning, especially methods that can be used as replacement for back-propagation often employed in supervised learning. While back-propagation is the state-of-the-art method to train deep neural networks, alternative approaches may have several advantages, e.g. being a more plausible learning method in biological systems, allowing discrete internal representations in artificial deep neural networks, and enabling higher levels of parallelism in distributed processing.

One core research question in this project is to obtain a better understanding of the underlying credit assignment problem that is intrinsic for all distributed representations such as deep neural networks. Improvements in how the credit (i.e. the penalty induced by a loss function) is assigned to network units will lead to faster learning methods, and also may be highly beneficial in the few-shot learning scenario.

The utilized method to train deep neural networks also reflects the underlying computational model of deep  networks. Training with back-propagation is connected with a pure feed-forward computational model lacking any feedback channel, and contrastive Hebbian learning uses a computational model that allows bidirectional feedback when determining the internal representation propagated through the network. Thus, different optimization methods for deep learning can also lead to different interpretations and therefore different ways of understanding and explaining deep neural architectures. Consequently, one goal of this project is to further explore computational models related to deep learning.

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:

Major Responsibilities
Your major responsibilities are to pursue your own doctoral studies. You are expected to develop your own scientific concepts and communicate the results of your research verbally and in writing, both in Swedish and in English. The position generally also includes teaching on Chalmers' undergraduate level or performing other duties corresponding to 20 per cent of working hours.     

Position Summary
Full-time temporary employment. The position is limited to a maximum of five years.

To qualify as a PhD student, you must have a master's level degree corresponding to at least 240 higher education credits in a relevant field (physics, mathematics or computer science).

The position requires sound verbal and written communication skills in Swedish and English. If Swedish is not your native language, you should be able to teach in Swedish after two years. Chalmers offers Swedish courses.

Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

Our Offer To You
Chalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg
Read more about working at Chalmers and our benefits for employees.

Application Procedure
The application should be marked with Ref 20190319 and written in English. The application should be sent electronically and be attached as pdf-files, as below:

CV: (Please name the document: CV, Family name, Ref. number)
• CV
• Other, for example previous employments or leadership qualifications and positions of trust.
• 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 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?

Other Documents:
• Copies of bachelor and/or master’s thesis.
• Attested copies and transcripts of completed education, grades and other certificates, eg. TOEFL test results.

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

Application Deadline: 28 June, 2019

For questions, please contact:
Christopher Zach,

In your application, please refer to