PhD students in machine learning for image generation

Updated: over 1 year ago
Deadline: 15 Aug 2022

Skilled and committed employees are a crucial factor in the success of Linköping University. And we need more of them. Our core expertise comes from teachers and researchers, but a successful university requires experienced and motivated employees in many fields. Everyone is important. We need to recruit many new employees thanks to, among all, an expansion in our research activity. We need you here. We look forward to receiving your application!

At the Department of Science and Technology, at the university’s Norrköping campus, we provide education and conduct research in physics and electronics, communications/logistics and media- and information technology. The department is recognised for its work in fields including logistics, visualisation and organic electronics. We combine academic excellence with fruitful collaboration with the Community.
Read more at https://liu.se/en/organisation/liu/itn

We are now looking for 1-2 PhD students in machine learning with a focus on generative deep learning, placed at the Division for Media and Information Technology at the Department of Science and Technology, Campus Norrköping.

The positions are part of the Wallenberg AI, Autonomous Systems and Software Program (WASP). You will take part in the WASP curriculum and benefit from its extensive network of other PhD students and senior researchers.

WASP is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. 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, please see: https://wasp-sweden.org/

Your work assignments
The research area for the advertised positions lies in the intersection of machine learning, deep learning, computer graphics and computer vision. The goal is to create synthetic image data with combinations of computer graphics and generative deep learning. The generated images will be used as training data in machine learning applications, for improving performance and robustness, or as a tool for anonymizing sensitive images. The developed methods will be tested in various applications, e.g. for medical imaging diagnostics. The project includes both basic research on the development of new image generation methods, as well as applied research to show the benefits of the new methods.

As a doctoral student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time.

Your workplace
You will work in the Division for Media and Information Technology at the Department of Science and Technology at Campus Norrköping. The division researches and conducts education in areas such as computer graphics, image analysis, scientific visualization and machine learning, at undergraduate, advanced and postgraduate levels.

Our research group consists of 20 PhD students, senior researchers and research engineers. We conduct research projects in areas spanning from deep learning and medical imaging, to computer graphics and computational photography.

Your qualifications
You have graduated at Master’s level, or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses, in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. Alternatively, you have gained essentially corresponding knowledge in another way.

You should also have good communication skills, excellent study results and sufficient knowledge of oral and written English. You must have documented experience of machine learning, and specifically deep learning. Experience in generative deep learning, computer graphics, and computer vision is particularly meritorious. The project involves both theoretical and applied work.

Great emphasis will be placed on personal qualities and suitability.

Terms of employment
When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at.

The employment has a duration of four years’ full-time equivalent. You will initially be employed for a period of one year. The employment will subsequently be renewed for periods of maximum duration two years, depending on your progress through the study plan. The employment may be extended up to a maximum of five years, based on the amount of teaching and departmental duties you have carried out. Further extensions can be granted in special circumstances.

Starting date
By agreement.

Salary and employment benefits
The salary of doctoral students is determined according to a locally negotiated salary progression.

More information about employment benefits at Linköping University is available here.

Union representatives
Information about union representatives, see Help for applicants.

Application procedure
Apply for the position by clicking the “Apply” button below. Your application must be received at latest August 15, 2022.

Applications and documents received after the date above will not be considered.

We welcome applicants with different backgrounds, experiences and perspectives - diversity enriches our work and helps us grow. Preserving everybody's equal value, rights and opportunities is a natural part of who we are. Read more about our work with: Equal opportunities .

We look forward to receiving your application!

Linköping university has framework agreements and wishes to decline direct contacts from staffing- and recruitment companies as well as vendors of job advertisements.


URL to this page
https://liu.se/en/work-at-liu/vacancies?rmpage=job&rmjob=19171&rmlang=UK



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