Postdoctoral researcher in statistical bioinformatics

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Ref nr: ORU 2.1.1- 04388/2020

The School of Medical Sciences is seeking a postdoctoral researcher in Statistical Bioinformatics, with application in biomedicine and psychology, for a fixed-term appointment (2 years).

Subject area

The position is in Medical Sciences, with special focus on Statistical Bioinformatics.


Biomedicine and psychology research generate many large datasets with need for integrated analysis, including genetic, molecular, clinical, lifestyle and registry data, with mechanistic, diagnostic and prognostic objectives as well as dedicated towards precision medicine for personalised treatment and prevention. Strong research environments in biomedicine and psychology (CVRC, NGBI, CHAMP) generate such data with accelerating pace, regarding both amount of data and their complexity. Their modeling and analysis, “making sense out of data”, is a very active research field.

The candidate will build and investigate statistical as well as mathematical/mechanistic models of biomedical/molecular processes on various scales, with machine learning methodology, based on dynamical data and connected to large-scale clinical data, molecular data, and national registry data on chronic pain both from clinical collaboration partners in Örebro, and multimodal pain services in Sweden. The project is transdisciplinary and includes business partners from the Life Science sector. As a postdoctoral researcher, you would join an interdisciplinary research environment comprised of statisticians, psychologists and physicians connected to the project. This project is hosted by the Functional Bioinformatics group at the School of Medical Sciences and is affiliated to the School of criminology, law, psychology and social work at Örebro University.

Örebro University is one of the fastest growing universities in Sweden with 17000 students and 1500 employees, and ranks among the top 500 universities in the world according to Times Higher Education 2019.

Duties and responsibilities

The appointment as a postdoctoral researcher is intended to enable persons who have recently been awarded their doctoral degree, to consolidate and develop primarily their research/artistic skills.

The applicant will be responsible for developing and investigating statistical bioinformatics models based on experimental data available within the various collaborating research environments relevant for a variety of mechanisms in inflammation research as well as factors associated with a variety of pain phenotypes. The applicant will engage in tight discussions for hypothesis development, model specification and adaptation, as well as generation of model predictions, in close collaboration with experimentally working biomedical researchers and clinicians. 


Eligible for the appointment as postdoctoral researcher are applicants holding a doctoral degree in (bio)physics, computer science, applied statistics, or in related subject areas, with close relation to medical or life sciences and experience in application and development of machine learning algorithms. The doctoral degree should have been awarded no more than three years prior to the application deadline. Candidates who have obtained their doctoral degree prior to that may however also be considered if special grounds exist (leave of absence due to illness, parental leave, clinical duties, an elected position in a trade union, or other similar circumstances

Assessment criteria

General assessment criteria include excellent interpersonal skills and an ability to cooperate as well as the ability and suitability otherwise required to perform the duties well. Particular importance shall be attached to the qualities enabling the candidate to contribute to the future development of both research and education. A demonstrated ability and desire to pursue an academic career is also of importance.

In addition, experience of statistical modelling and data analysis is crucial, preferably with application within the (bio)medical sciences.  Previous research within mixed model analysis in the life sciences is preferred. Since the project will be conducted in close collaborations with other professions and non-academic partners, a cooperative mindset is of great importance. The applicant should also be highly organized, able to meet deadlines, have a clear sense of responsibility and be goal oriented.


The position is a full-time position for a fixed term of two years. The salary depends on the successful candidate’s qualifications and experience.

For more information, please contact Prof. Dirk Repsilber, This is an email address, Prof. Hugo Hesser,  This is an email address or Prof. Allan Sirsjö, allan. This is an email address, or Prof. Robert Brummer, This is an email address.

Örebro University actively pursues an equal work environment and values the qualities that diversity adds to our operations.

Assessment criteria/Application

The application is made online. Click the button “Apply” to begin the application procedure.

For the application to be complete, the following electronic documents must be included:

  • A covering letter, outlining how you believe you can contribute to the continued development of Örebro University
  • CV with a relevant description of your overall qualifications and experience
  • An account of research/artistic qualifications
  • Copies of relevant course/degree certificates and references verifying eligibility and criteria met
  • Scientific publications for consideration (maximum of 10) (Not only publication list.)

Only documents written in Swedish, English, Norwegian or Danish can be reviewed.

The application deadline is September 30 2020. We look forward to receiving your application!

We decline any contact with advertisers or recruitment agencies in the recruitment process.

As directed by the National Archives of Sweden (Riksarkivet), Örebro University is required to deposit one file copy of the application documents, excluding publications, for a period of two years after the appointment decision has gained legal force.