The University of Oslo is Norway’s oldest and highest rated institution of research and education with 28 000 students and 7000 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society. 

The Department of Informatics (IFI) is one of nine departments belonging to the Faculty of Mathematics and Natural Sciences.. IFI is Norway’s largest university department for general education and research in Computer Science and related topics. The Department has near 950 students on bachelor level, near 450 master students, and over 180 PhD students. The overall staff of the Department is close to 250 employees, about 200 of these are full time positions. The full time scientific staff is 60, mostly Full/Associate Professors.

Postdoctoral Research Fellowships in Image analysis and classification

At the Department of Informatics, up to three positions as Postdoctoral Research Fellow (SKO 1352) are available in the Digital Signal Processing and Image Analysis Group.

The fellowships are funded by the project DoMore!:In silico Pathology- Improving diagnosis by utilizing Big Data and software-driven automation of pathology. DoMore! is based on a collaboration between the Institute of Cancer Genetics and Informatics at Oslo University Hospital and the Department of Informatics at the university, and is funded by The Research Council of Norway as one of the council’s three “ICT lighthouse projects”. The project aims at radically improving prognostication and hence treatment for cancer patients by developing digital tools for pathology.

The fellowships are for a period of 2 years. Starting dates are as soon as possible and no later than 01.10.2018. No one can be appointed as a Postdoctoral Research Fellow for more than one specified period at the same institution.

Project description

The postdoctoral fellows will contribute within the work-packages in the DoMore! project. The development of new methods in image analyses and classification, including Deep learning methods, will be central. The biomedical challenges include automatic tumor delineation (identification of tumor regions in tissue sections) and tumor grading (assessing how abnormal the tumor tissue is based on microscopy images). Moreover, the project aims at developing texture-based and adaptive segmentation methods for cell nuclei in tissue sections, methods for handling of touching and partially overlapping cell nuclei and an automatic segmentation evaluation and quality control system. Furthermore, the project aims at automating ploidy analysis (the assessment of whether DNA content is normal or abnormal) and nucleotyping (characterization of chromatin organization in cell nuclei in tissue sections) in tissue sections. The developed methods should be implemented in a decision support framework.


The Faculty of Mathematics and Natural Sciences has a strategic ambition of being a leading research faculty. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

The main purpose of post-doctoral research fellowships is to qualify researchers for work in top academic positions within their disciplines.

The candidates must have a PhD or other corresponding education equivalent to a Norwegian doctoral degree in informatics/computer science, statistics, machine learning, image and signal processing or related areas. Previous experience working with medical or biological images and data is also an advantage. For two of the positions, proven knowledge and ability in deep learning frameworks and practical use of neural nets is absolutely required, and knowledge of standard computer vision techniques and experience in implementing, analysing, and optimizing scientific applications for image analysis is required. For the third position, advanced knowledge of machine learning and decision support is required. Proficiency in scientific computing languages is required, and experience with parallel programming environments is a plus.

Please also refer to the regulations pertaining to the conditions of employment for post-doctoral fellowship positions. A good command of English is required.

We offer:

  • Salary, NOK 517 700 - 569 000 per year, depending on qualifications and seniority, position code 1352
  • A professionally stimulating working environment
  • Attractive welfare benefits and a generous pension agreement, in addition to Oslo’s family-friendly environment with its rich opportunities for culture and outdoor activities

The application must include:

  • ŠApplication letter
  • ŠStatement of purpose: scholarly interests and goals
  • ŠCV (summarizing education, positions, pedagogical experience, administrative experience and other qualifying activity)
  • ŠCopies of educational certificates, transcript of records and letters of recommendation
  • ŠA complete list of publications and copies of up to 5 academic works that the applicant wishes to be considered by the evaluation committee
  • ŠNames and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number) Please remember that all documents should be in English ora Scandinavian language.

The application with attachments must be delivered in our electronic recruiting system, please follow the link “apply for this job”. Foreign applicants are advised to attach an explanation of their University's grading system.

In accordance with the University of Oslo's equal opportunities policy, we invite applications from all interested individuals regardless of gender or ethnicity.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results a.o.

For more information, contact:

Professor Fritz Albregtsen, +47 911 63 005

Professor Knut Liestøl, +47 957 22 532

For questions about the recruitment system, please contact HR Officer Helene Beate Jansen, +47 22857196,

Søk stillingen

Om stillingen

  • Søknadsfrist
    1. februar 2018
  • Arbeidsgiver
    University of Oslo
  • Nettside
  • Kommune
  • Jobbnorge-ID
  • Intern-ID
    2018/553 - 1352
  • Omfang
  • Varighet

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