Postdoctoral position in deep learning based sparse view tomography
Uppsala University is a comprehensive research-intensive university with a
strong international standing. Our ultimate goal is to conduct education and
research of the highest quality and relevance to make a long-term difference
in society. Our most important assets are all the individuals whose curiosity
and dedication make Uppsala University one of Sweden's most exciting
workplaces. Uppsala University has over 45,000 students, more than 7,000
employees and a turnover of around SEK 7 billion.
At the Division of Systems and Control, we develop both theory and concrete
tools for learning, reasoning, and acting based on data. An overarching goal
is for both humans and machines to better understand the complexity of the
real world. Probabilistic models form a central part of our research, allowing
us to systematically represent and cope with the uncertainty inherent in most
data. Data and learning algorithms are also important components of our
research. It remains a major challenge to develop efficient and accurate
learning algorithms capable of handling high-dimensional models, data rich
applications, complex model structures, and diverse data sources that arise in
many of the data analysis problems that we are currently facing.
We have a wide network of strong international collaborators all around the
world, for example at the University of Cambridge, University of Oxford,
University of British Columbia, University of Sydney, University of Newcastle
and Aalto University. There are also ample opportunities for collaborations
with other leading machine learning groups in Sweden and Europe, through our
affiliations with WASP (https: // wasp-sweden.org/) and the ELLIS society
(https: // ellis.eu/), respectively.
Read more about our benefits and what it is like to work at Uppsala University
We offer a two-year postdoctoral fellowship based on a grant from Kjell and
Märta Beijer Foundation and the Tandem Forest Values programme at the Royal
Swedish Academy of Agriculture and Forestry.
The position includes research into theory and development of deep learning
algorithms for computer vision regression tasks in tomographic image
reconstruction, meaning that input is noisy sparse view tomographic data of an
object. One aim is to extend energy-based models for deep probabilistic
regression to such a setting, e.g., by including a handcrafted physics model
for generating data from an image. Work will be spearheaded by the need to
detect and locate interior imperfections (cracks, knots, metallic inserts,
etc.) of logs from sparse view tomographic data. This application is part of
a collaboration with a larger international project supported by the Academy
of Finland involving researchers at LUT-University and University of Oulu with
an overall goal of developing methods for image guided optimization of the
sawline in processing of forest logs. It is also part of a recently initiated
collaboration with researchers at the Wood Science and Engineering at Luleå
University of Technology.
The research will be pursued at the Department of Information Technology at
Uppsala University. As a postdoctoral fellow, you will benefit from the strong
research environments at Uppsala University in machine learning.
PhD degree in mathematics, signal processing, computer science, or
computational physics/engineering or a foreign degree equivalent to a PhD
degree in mathematics, signal processing, computer science, or computational
physics/engineering. The degree needs to be obtained by the time of the
decision of employment. Those who have obtained a PhD degree three years prior
to the application deadline are primarily considered for the employment. The
starting point of the three-year frame period is the application deadline. Due
to special circumstances, the degree may have been obtained earlier. The
three-year period can be extended due to circumstances such as sick leave,
parental leave, duties in labour unions, etc.
The candidate must have a strong background from machine learning or
signal/image processing with experience from software development in
scientific computing or machine learning using Python and/or C/C++. Finally, a
successful candidate must be strongly motivated and have the capability to
work independently as well as in collaboration with members of the research
Experience from tomographic image reconstruction is highly desirable. An
additional advantage is a research track record with publications at leading
conferences in machine learning. As a person, you are creative, thorough and
have a structured approach. When selecting among the applicants we will assess
their ability to independently drive their work forward, to collaborate with
others, to have a professional approach and to analyze and work with complex
problems. Great emphasis will be placed on personal characteristics and
About the employment
The employment is a temporary position of 2 years according to central
collective agreement. Scope of employment 100 %. Starting date upon agreement,
but preferably no later than 31 March 2022 or as agreed. Placement: Uppsala
Application: The application must contain:
A curriculum vitae (CV),
A copy of relevant grade documents (translated into Swedish or English),
A list of publications
Up to five selected publications in electronic format
A research statement describing your past and current research (max 1 page) and a proposal for future activities (max 1 page).
Contact information for two references.
A cover letter briefly describing your motivation for applying for this position and the earliest possible employment date (max 1 page).
For further information about the position, please contact: Professor
Ozan Öktem (phone: +46-733-52 2185, e-mail: firstname.lastname@example.org) or
Professor Thomas Schön (phone: +46-18-471 2594, e-mail:
Please submit your application by 4th February 2022, UFV-PA 2021/5142.
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Please do not send offers of recruitment or advertising services.
Submit your application through Uppsala University's recruitment system.
Placement: Department of Information Technology
Type of employment: Full time , Temporary position longer than 6 months
Pay: Fixed salary
Number of positions: 1
Working hours: 100%
County: Uppsala län
Union representative: Seko Universitetsklubben email@example.com
Number of reference: UFV-PA 2021/5142
Last application date: 2022-02-04