PhD Research Fellow in Biostatistics

About Company
University of Oslo
Job Info
Job Status: Expired
No of Vacancies: 1
Date Posted: November 14, 2017
Expiry Date: November 23, 2017
Job Type: PhD
Job Level: Any
Years of Experience: 2
Salary Info
Salary Type: Min-Max
Salary: NOK 436 900-NOK 490 900
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Applications are invited for a PhD student position for a period of 3 years at the Oslo Centre for Biostatistics and Epidemiology (OCBE), Department of Biostatistics, University of Oslo.

This is an opportunity to join one of Europe’s most active biostatistics groups at an exciting time. Currently, OCBE includes nine tenured professors and associate professors, twelve researchers, and several post-doctoral fellows and PhD students, making up a group of about 50. OCBE is internationally recognized, with interests spanning a broad range of areas (including time-to-event models, data integration, causal inference, statistical genomics, Bayesian inference, informative missingness and measurement error models, epidemiological studies of lifestyle and chronic diseases, stochastic models for infectious diseases, high dimensional data and models) and numerous collaborations with leading bio-medical research groups nationally and internationally.

The PhD position is funded by the European Research Council through the Advanced grant project “SCARABEE”.

Job description

The position is targeted towards development and application of novel inference methods for intractable statistical network models in genomics.

The research fellow must take part in the Medical Faculty’s approved PhD program and is expected to complete the project within the set fellowship period. The main purpose of the fellowship is research training leading to the successful completion of a PhD degree.

For more information, please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

Qualification requirements

Applicants must hold a Master’s degree or equivalent in statistics or computer science prior to starting in this job. They should also have documented research experience about computational inference for high-dimensional Markov network models and function optimization using GPU acceleration.

Applicants should have fluent oral and written communication skills in English.

We offer

How to apply

The application must include:

  • A one-page text describing current research interests and potential contributions to the planned project
  • CV summarizing education, positions held, details of  academic work, pedagogical and administrative experience and other qualifying activities
  • List of publications
  • Copies of educational certificates and transcripts of records
  • Names and contact details of 2-3 referees stating relation to candidate, e-mail and telephone number

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).

When evaluating the application, emphasis will be given to the applicant’s academic and personal prerequisites to carry out the project. Applicants may be called in for an interview.

Formal regulations

The fellowship requires admission to the PhD program at the Medical Faculty at the UiO. For more information see:

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 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 agreement for all employees, aiming to secure rights to research results and intellectual property.

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

Deadline: 23.11.2017

Contact persons:

Professor Jukka Corander,