School of Engineering Sciences at KTH

Job description

The position is part of a collaborative project with the Division of Wood Science and Engineering at Luleå university of technology, whose overall goal is to develop theory and algorithms for image-guided optimisation of the sawline. Specific tasks is to develop and implement physics aware deep neural networks for tomographic 3D image reconstruction with partially unknown acquisition geometry. Prototypes will be implemented as components in ODL ( that offers a seamless coupling between frameworks for tomography (ASTRA) and deep learning (PyTorch).

Link with further information:

What we offer

  • A position at a leading technical university that generates knowledge and skills for a sustainable future
  • Engaged and ambitious colleagues along with a creative, international and dynamic working environment
  • Work in Stockholm, in close proximity to nature
  • Help to relocate and be settled in Sweden and at KTH
  • A research environment in mathematical image science with world leading expertise in development and application of deep learning in tomographic image reconstruction.
  • Participation in a collaboration that offers access to unique data and world leading expertise in imaging wood and integration of such technologies digitization of forestry industry.

Read more about what it is like to work at KTH



  • A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
  • Doctoral degree is in mathematics, computational science, image/signal-processing, computer science, physics, or chemistry.
  • Documented research expertise on tomographic image reconstruction or deep learning.
  • Documented experience from implementing deep learning models.
  • English language skills that meet requirement set by the Swedish Council for Higher Education for admission to all higher education institutions in Sweden, which includes ability in English equivalent to English B/6, since it is needed in the daily work.

Preferred qualifications

  • A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
  • It's commendable if you have documented research expertise on deep learning for tomographic image reconstruction.
  • We prefer that you have documented research expertise from deep learning in sciences and engineering or image processing.
  • We prefer that you have experience from large scale numerical computations.
  • We prefer that you have experience from collaborative software development.
  • As a person you are highly motivated and can work independently.
  • Teaching abilities
  • Awareness of diversity and equal opportunity issues, with specific focus on gender equality
  • Collaborative abilities

Great emphasis will be placed on personal competency.

Trade union representatives

You will find contact information to trade union representatives at KTH's webbpage.


Log into KTH's recruitment system in order to apply to this position. You are the main responsible to ensure that your application is complete according to the ad.

The application must include:

  • CV including relevant professional experience and knowledge.
  • List of publications, indicate the three most relevant for the position.
  • Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
  • Research statement (max 2 pages) that outlines how you envision your part in the project. Try to point to concrete areas where you think you can contribute.

Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).

About the employment

The position offered is for, at the most, two years.

A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.


Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

For information about processing of personal data in the recruitment process please read here.

We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.

Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.

Type of employment Temporary position
Contract type Full time
First day of employment According to agreement
Salary Monthly salary
Number of positions 1
Full-time equivalent 100 %
City Stockholm
County Stockholms län
Country Sweden
Reference number S-2023-0640
  • Ozan Öktem,
Published 19.Apr.2023
Last application date 01.Sep.2023 11:59 PM CEST

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