About the position
One position as PhD Research Fellow in semi-supervised deep learning is available at dScience – Centre for Computational and Data Science, University of Oslo. The PhD position is a part of their machine learning program, see
The position is located at the Digital Signal Processing and Image Analysis (DSB) group at the Department of Informatics, University of Oslo, and the candidate will work in close collaboration also with the Institute for Cancer Genetics and Informatics (ICGI) at Oslo University Hospital.
The fellowship period is three (3) years and devoted to carrying out a project entitled Improving predictions in histopathology using semi-supervised learning under the presence of domain shifts.
Candidates may be offered one additional year by the Department of Informatics; the 4-year position then entails a compulsory workload of 25% that may consist of teaching and supervision duties.
Starting date is no later than October 1, 2021. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.
Job description
dScience is a new cross-discipline research centre at the University of Oslo.
The research challenges that the candidates will be addressing in this project are related to:
- learning from limited and partially-labelled training data,
- generalization in the presence of domain shift,
- outlier detection (semi-supervised), and
- efficient approaches for whole-slide analysis
The core of the research work will be on semi-supervised deep learning method development. The methods will be applied to real data from histopathology and related disciplines. A detailed plan for the PhD period will be defined based on the background of the candidate and the project needs.
The candidate will be part of the dScience research centre, the DSB group, and the ICGI. The candidate will be expected to actively engage in collaborative research with other members of the centre and the research groups.
Qualification requirements
The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. 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.
- A Master’s degree or an equivalent qualification in Computer Science, preferably with a specialization in machine learning, deep learning, or image analysis
- A background in physics/statistics/applied mathematics/electrical engineering can also be considered given that the candidate has formal competence in machine learning or deep learning
- A foreign completed degree (M.Sc.-level) must correspond to a minimum of four years in the Norwegian educational system
- Documented knowledge and experience in Python programming and deep learning frameworks like TensorFlow or PyTorch are required.
- A solid and documented background in machine learning, mathematics, linear algebra, and statistics is also required.
- It will be considered as an advantage to have experience in high performance computing and tooling in Linux, handling whole-slide image data, writing papers in highly ranked conferences (rank B or better) or scientific journals, writing manuscripts in LaTeX, overview over ongoing research in deep learning, and coding skills in C++ or Java.
Candidates without a Master’s degree have until August 15, 2021 to complete the final Master of Science exam.
Grade requirements:
The norm is as follows:
- The average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
- The average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
- The Master’s thesis must have the grade B or better in the Norwegian educational system
- Fluent oral and written communication skills in English
- English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements:
Desired skills:
- A strong interest to publish in highly ranked journals and conferences.
The purpose of the fellowship is research training leading to the successful completion of a PhD degree.
The fellowship requires admission to the PhD program at the Faculty of Mathematics and Natural Sciences. The application to the PhD program must be submitted to the department no later than two months after taking up the position. For more information see:
We offer
- Salary NOK 482 200 – 526 000 per year depending on qualifications and seniority as PhD Research Fellow (position code 1017)
- Vibrant international academic environment
- Attractive and a generous pension agreement
- Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities
How to apply
The application must include:
- Cover letter including a description of scientific interests and the motivation for applying for the position (max. 2 pages)
- CV (summarizing education, positions and academic work - scientific publications)
- Copies of educational certificates, transcript of records and letters of recommendation
- Documentation of English proficiency if needed (please see admission criteria)
- List of publications and academic work that the applicant wishes to be considered by the evaluation committee
- Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)
- Applicants who are interested in teaching need to add to this application a description of their motivation for teaching
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. Please note that all documents should be in English (or a Scandinavian language).
Applicants will normally be called in for an interview.
Formal regulations
Please see the for appointments to Research Fellowships at the University of Oslo.
No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.
According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.
The appointment may be shortened/given a more limited scope within the framework of the applicable guidelines on account of any previous employment in academic positions.
The University of Oslo has an for all employees, aiming to secure rights to research results etc.
Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. We also want to have employees with diverse expertise, combinations of subjects, life experience and perspectives. We will make adjustments for employees who require this.
If there are qualified applicants with special needs, gaps in their CVs or immigrant backgrounds, we will invite at least one applicant in each of these groups to an interview.
Contact information
For further information, please contact Associate Professor Alexander Binder, e-mail: Logg inn for å se kontaktinformasjon or Associate Professor Andreas Kleppe, e-mail: Logg inn for å se kontaktinformasjon
For technical questions regarding the recruitment system, please contact HR Adviser Torunn Standal Guttormsen, e-mail: Logg inn for å se kontaktinformasjon, phone: Logg inn for å se kontaktinformasjon.
