Postdoctoral Fellowship in Learning Technologies and Multimodal Analytics

Trondheim, Norway
11 Sep 2018
End of advertisement period
01 Oct 2018
IE 163-2018
Contract Type
Full Time

The Faculty of Information Technology and Electrical Engineering (  at the Norwegian University of Science and Technology (NTNU) has a vacancy for one postdoctoral fellow position within learning technologies to support STEM education at the Department of Computer Science (IDI) (             

An appointment as postdoctoral fellow is for a term of 3 years with duties equivalent to 33%. The position of postdoctoral fellow is a fixed term position with the primary objective of qualifying for work in top academic posts.

Information about the department

The Department of Computer Science currently employs 30 full time professors, 60 associate/assistant professors, 19 adjunct professors, 37 postdocs/researchers, 90 PhD students, and 24 technical/administrative staff. The department holds a wide portfolio of highly competitive projects in the area of learning technologies and innovative education ( and has recently been awarded with the nationwide status of Centre for Excellence in Information Technology Education.

Work description

The candidate will be a member of the Information Systems and Software Engineering research group and work with the “FUTURE LEARNING: Orchestrating 21st Century Learning Ecosystems using Analytics” project.

FUTURE LEARNING is a Norwegian Research Council funded project under Research and Innovation in the Educational Sector (FINNUT) program. FUTURE LEARNING aims at producing research that contributes towards the orchestration of multiple technologies to support better learning and teaching, and contributes to the growing international research literature. Our interdisciplinary and international team will carry out empirical-oriented research to develop new knowledge about how analytics allow us to better orchestrate different e-learning tools and learning practices. FUTURE LEARNING focuses on:

a) an analysis of the prior empirical and theoretical knowledge to address requirements for efficient learning orchestration and
b) iteratively develop, use and evaluate a framework for efficient orchestration of 21st century learning ecosystems.

In particular, the proposed research seeks to explore, with both qualitative and quantitative data sources, practical and technical knowledge for improving 21st century learning ecosystems.

The successful candidate will work with the following task:

  • Plan and conduct empirical studies in the area of learning technologies
  • Analyze collected data and write up research articles related to the use and/or impact of learning analytics on teaching and learning

The position requires strong English oral and writing skills as the candidate will be interacting with a team of international researcher and the job will include progress reports in English.


The position requires strong English oral and writing skills as the candidate will be interacting with a team of international researcher. The job will include providing several progress reports in English.

If the applicant’s PhD is not from an English-speaking country, the following tests can be used as documentation: TOEFL, IELTS and Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:

  • TOEFL: 600 (paper-based test), 92 (Internet-based test)
  • IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted)
  • CAE/CPE: grade B or A

In addition, the candidates should have the following qualifications:

  • PhD degree in learning technologies, human-centered computing, learning analytics or equivalent is required
  • Hands-on experience with Learning Analytics, Information Visualization and Data Science tools and techniques
  • Web development and data analysis programming skills
  • Good understanding of quantitative and qualitative analysis methods
  • Demonstrated research capability via a good publications record
  • Demonstrated ability to work independently as well as collaboratively
  • Excellent written and oral communication skills

The following qualifications will be considered as an advantage:

  • Expertise with heterogeneous, multi-scale and multimodal learning analytics
  • Experience with participation in research projects (e.g., EU, national)

Emphasis will be put on personal qualities and potential as a researcher. High importance will also be attached to personal communication and cooperation skills.

Potential successful candidate will be interviewed via Skype or other means.

We can offer

  • Becoming member of a top-tier international research group
  • An informal and friendly workplace with dedicated colleagues
  • Academic challenges
  • Attractive schemes for housing loan, insurance and pensions in the Norwegian Public Service Pension Fund.

The Faculty of Information Technology and Electrical Engineering want to attract outstanding and creative candidates who can contribute to our ongoing research activities. We believe that diversity is important to achieve a good, inclusive working environment. We encourage all qualified candidates to apply, regardless of the gender, disability or cultural background. NTNU wishes to increase the number of woman in its workforce, and female candidates are therefore encouraged to apply.

Salary conditions

The position is in code 1352 Post doctor, salary grade range 59-74 in the Norwegian State salary scale, gross NOK 515.200 – 682.200 per year, depending on qualifications. A deduction of 2% is made as a statutory contribution to the Norwegian Public Service Pension Fund.

General information

The appointment is subject to the conditions in effect at any time for employees in the public sector.

As far as possible, the State workforce should reflect the diversity of the population. Goals of our personnel policy therefore include a balanced distribution in terms of age and gender as well as recruitment of people of immigrant background.

Under Section 25 of the Freedom of Information Act, information about the applicant may be made public even if the applicant has requested not to have his or her name entered on the list of applicants.


The application must contain:

  • One-page cover letter including an explanation of how your research interests and background would fit the position
  • Information about education and relevant experience (academic CV)
  • Certified copies of academic diplomas and certificates
  • Applicants from universities outside Norway are kindly requested to send a diploma supplement or a similar document, which describes in detail the study and grading system and the rights for further studies associated with the obtained degree
  • A short essay (up to 2000 words) describing his/her view of the main research challenges in learning technologies to support science education
  • The PhD thesis and other publications (Max 5) relevant to the research scope and any other work which the applicant wishes to be taken into account should clearly indicate the applicant’s contribution
  • Names and contact information of at least two references

Incomplete applications will not be taken into consideration.

The application must be sent electronically as one combined PDF file via this page (

For further information, please contact Associate Professor Michail Giannakos, email:, phone: +47 73590731 or head of the department Professor John Krogstie, e-mail:, phone +47 93417551.

For information about processing of applications, please contact Senior Executive Officer Anne Kristin Bratseth, phone +47 73 59 67 15, e-mail:

Mark the application IE 163-2018

Deadline for applications: 2018-10-01

About this job

  • Deadline Monday, October 1, 2018
  • Employer NTNU - Norwegian University of Science and Technology
  • Website
  • Municipality Trondheim
  • Place of service Trondheim
  • Jobbnorge ID 157320
  • Internal ID 2018/29792
  • Scope Fulltime
  • Duration Temporary

About applications

  • Applications on this job are registered in an electronic form on
  • You must complete: Standard CV
  • Please refer to where you first saw this job advertised!

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