Postdoctoral Research Fellow in Statistics / Data Science University of Oslo, Department of Mathematics

Postdoctoral Research Fellow in Statistics / Data Science


Job description

One position as Postdoctoral Research Fellow (SKO 1352) in statistics is available at the Department of Mathematics at the University of Oslo. The fellowship period is for three years, with a starting date as soon as possible in 2018. No one can be appointed as Postdoctoral Research Fellow for more than one specified period at the same institution.


This is an opportunity to join one of Europe's most active statistics communities at an exciting time. Currently, the Department includes 10 tenured faculty members in statistics and several PhD students, making up a group of about 25. Statistics at UiO is internationally recognized, with interests spanning a broad range of areas (including space-time data, model selection, mathematical statistics, time-to-event models, data integration, copula and dependence models, statistical genomics, Bayesian inference, stochastic models, high dimensional data and models) and numerous collaborations with leading research groups internationally. In the 2012 national research evaluation, statistics at UiO was judged as excellent by an international committee. The research group is central in the Center for Research-based Innovation ‘BigInsight’, to which the present post doctoral fellowship will be affiliated.


BigInsight is a research partnership with the Norwegian Computing Center, other statisticians at the University of Oslo and important industrial and public innovation partners including ABB, DNB, DNV-GL, Gjensidige, Norsk Hydro, NAV, Skatteetaten, Statistics Norway and Telenor. BigInsight develops original statistical and machine learning methodologies and analytical and computational tools to extract knowledge from complex and big data, with focus on novel personalised solutions and sharper predictions of transient behaviours. BigInsight and the University of Oslo offer a lively and socially rewarding environment, with many common activities, a broad visitor program, as well as solid travel funding.


The position will be dedicated to the BigInsight Innovation Objective ‘Sensor Systems’. The analysis of sensor data is becoming increasingly important and challenging as sensor and AI technology emerge. The Sensor Systems project has focus on sensor data from the maritime sector through the industrial partners ABB and DNV-GL. The project is targeted to develop multi-sensor, multi-scale statistical methods for condition and performance monitoring in real time, including anomaly prediction, change point detection, and uncertainty quantification. The post doctoral fellow will be part of a large team consisting of three PhD students, faculty staff and researchers from partner institutions.


In collaboration with faculty members and partners at ABB and DNV-GL, the post doctoral fellow is expected to contribute to the management and organisation of the project, by taking direct responsibilities in the administrative and leading tasks of the project. She/he will be responsible for progress, developing methodology, implementing algorithms and producing scientific results of substantial interest, published in top peer-reviewed scientific journals.


Bilde av forskere som smiler

More about the position

The appointment is a fulltime position and is made for a period of up to three years (10% of which is devoted to required duties, usually in the form of teaching activities).


The main purpose of the fellowship is to qualify researchers for work in higher academic positions within their disciplines.


Qualification requirements

Applicants must have a PhD in statistics, or in a related quantitative subject with proven competence in statistics and/or machine learning. Excellent results in the MSc and PhD studies are required. Experience with sensor data, streaming data, signal processing and/or time series data will be an advantage but is not required. Working language is English, and a good command of English is required. Candidates to the position will have some experience and/or clear potentials to initiate, develop and manage an independent scientific programme. The role holder will possess sufficient administrative skills to manage projects and contribute to the common workload of the project. Candidates must demonstrate team spirit in developing their research, with strong interpersonal skills. Proficiency with programing languages (R, Matlab, Python, C++ or others) is necessary.


The main purpose of post-doctoral research fellowships is to qualify researchers for work in top academic positions within their disciplines. Please also refer to the regulations pertaining to the conditions of employment for post-doctoral fellowship positions:


The applicant should arrange for two letters of reference to be sent directly by e-mail to professor Ingrid K. Glad ( within the application deadline.


We offer


  • salary NOK 490 900 - 569 000 per annum depending on qualifications in position as Postdoctoral Research Fellow (position code 1352)
  • Three* years full time employment
  • Annual paid leave for 5 weeks, plus public holidays
  • A professionally stimulating working environment
  • Comprehensive pension and health insurance administered by the Government Pension Fund (SPK) and the Norwegian Labour and Welfare Administration (NAV). For more welfare benefits, see:


How to apply

The application must include

  • A short application letter
  • A (1 page) statement about research interests related to this specific project
  • CV (summarizing education, positions, pedagogical experience, administrative experience and other qualifying activity)
  • Copies of educational certificates, transcript of records
  • A complete list of publications and academic works
  • Names and contact details of two references who have been asked to send reference letters directly to Ingrid K. Glad (
  • Foreign applicants are advised to attach an explanation of their university’s grading system


The application with attachments must be delivered in our electronic recruiting system. 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.


In assessing the applications, special emphasis will be placed on the documented, academic qualifications, the project description (whenever this is required in the call for applicants), and the quality of the project as well as the candidates motivation and personal suitability. Interviews with the best qualified candidates will be arranged.
It is expected that the successful candidate will be able to complete the project in the course of the period of employment.


Formal regulations

Please see the guidelines and regulations for appointments to Postdoctoral fellowships at the University of Oslo.


No one can be appointed for more than one specified period at the same institution.

According to the Norwegian Freedom and 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 University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.


The University of Oslo aims to achieve a balanced gender composition in the workforce and to recruit people with ethnic minority backgrounds.


Contact information

For further information please contact:

Professor Ingrid K. Glad


For question regarding the recruitment system, please contact:

HR Officer Ørjan Pretorius




About the University of Oslo

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.


Department of Mathematics is part of the Faculty of Mathematics and Natural Sciences. The Department is engaged in research covering a wide spectrum of subjects within mathematics, mechanics and statistics.


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