Faculty of Health Sciences , Department of Physiotherapy

Oslo Metropolitan University is Norway's third largest university with almost 22,000 students and over 2,500 employees. We have campuses in central Oslo and at Romerike. OsloMet educates students and conducts research that contributes to the sustainability of the Norwegian welfare state and the metropolitan region.

The Faculty of Health Sciences consists of five departments and offers study programmes on all levels, including PhD. The faculty has about 6000 students and nearly 600 members of staff.

The Center of Intelligent Musculoskeletal Health (CIM) have a vacancy for a PhD Fellowship. The PhD fellowship will be offered for a period of three years, in a 100% position, and will be available from 1st of December 2021.

The Center of Intelligent Musculoskeletal Health (CIM) was recently approved as one of five excellent academic environments at OsloMet. The CIM will represent an ecosystem for user representatives, higher education scholars and researchers across specialties; in the Musculoskeletal research group, at OsloMet Artificial Intelligence Lab at the Faculty of Technology, Art and Design, and national and international research partners.

Researchers affiliated with the CIM conduct high-quality research on musculoskeletal health in a life course perspective, embracing adolescents, young adults, adults, and older people. Among the central goals of the CIM is to bring together experts in technological science, health science and social science to conduct epidemiological and intervention research using advanced methods, including Artificial Intelligence (AI) and Machine Learning (ML) technologies. The CIM staff aims to develop, evaluate, and implement effective innovative and practical solutions to improve the musculoskeletal health of individuals and the population. The CIM research activities intersect three core areas:

  • Epidemiology and Clinical Research
  • Intelligent Health and Innovation
  • Implementation and Dissemination

Area of research

Spinal disorders are known as the leading cause of non-fatal health loss worldwide for nearly three decades. Years lived with disability (YLDs) for low back pain increased by 18% from 2007 to 2017. Spinal disorders cause activity limitation and work absence with subsequent economic burden on individuals, families, communities, industry, health services and governments. The persistence of spinal disorders is a considerable challenge for health systems and economies not equipped to care for the increase in an ageing population.

Research into better prevention and treatment for spinal disorders currently moves “one-size-fits-all” approaches to personalized medicine and healthcare, where the goal is to tailor the best treatment for the patient based on their unique biological, psychological, and social characteristics. The scope of the AID-Spine project, part I, is to use our large surveys, administrative and specific health registers to investigate risk and prognostic models that form the basis for precise clinical co-decisions support tools and interventions, and which can be implemented into practice in order to provide more individual-based and personalized treatments. Norway has multiple nationwide health registries with possibility for linkage between registries, and integration of data from different registries can pave the way for powerful research in terms of validity and statistical power. We will use powerful methods such as statistical machine learning to process these large and complex data.

Therefore, the primary objective of AID-Spine part I is to use machine learning methods on large survey and health registry data in order to identify people with different treatment trajectories and health outcomes due to a spinal disorder. The AID-Spine project has three work packages and four overarching research questions: 1) what characterizes patients with different treatment trajectories for spinal disorder(s) and who is at risk for receiving spine surgery as compared to conservative treatment? 2) what characterizes patients who achieve a minimal important change after conservative and/or surgical treatment? 3) how valid are these risk and prognostic models when tested in external data sets? and 4) how can these risk and prognostic models be implemented into personalized, meaningful AI-based clinical co-decision tools and/or interventions?

The PhD-project is expected to encompass scientific investigations related to primarily research question 1 and 2, which should be reported in at least three scientific papers of which the PhD fellow is the first author. Parts of the PhD-project might also be related to research question 4, if that is of large interest for the actual PhD candidate. For further details required in the proposal, please contact the project leader, professor Margreth Grotle.

Qualification requirements

We are looking for candidates that must:

  • by the end of the recruitment process, have completed a Master’s degree in medicine, health science or computer science (equivalent to 120 credits) with a grade B or better
  • have basic knowledge of statistical methods (at Master level)
  • have experience from statistical analyses
  • be proficient in written and spoken English

It is an advantage if you

  • have conducted research on spinal disorders previously
  • have worked with large datasets
  • have published a paper within this research field

Desired personal skills

  • ability to work interdisciplinary and independently
  • ability to work systematically and under pressure
  • ability to finish tasks
  • motivation for contribution in the field of research
  • skills and interest in public dissemination of research

It is important to OsloMet to reflect the population of our region, and all qualified candidates are welcome to apply. We make active efforts to further develop OsloMet as an inclusive workplace and to adapt the workplace if required. You are also welcome to apply for a position with us if you have experienced periods where you have not been in work, education or training.

Application

In order to be considered for the position you must upload the following documents together with your online application by the final date for the application:

  • Cover letter, stating your reasons for applying and provide reasons for why you are particularly qualified for this PhD fellowship position.
  • CV
  • All pages of all certificates/diplomas. The certificates/diplomas should include ECTS grades (A–F). Please note that a description of your country’s/university’s grading system must be included with the transcripts. This must be an official document with the seal of the university. Foreign diplomas must be translated into English by the degree-conferring institution. Education from outside Norway should be recognised in advance by the Norwegian Agency for Quality Assurance in Education (NOKUT), and an authorized copy of the letter of recognition should be enclosed.
  • Master's degree
  • List of other publications
  • Applicants whose first language is not English must document their language skills by means of an official test (does not apply to applicants from the Nordic countries). The following tests are considered valid documentation: TOEFL, IELTS (academic version), Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Your test results must, as a minimum, be:

-TOEFL: 600 (paper-based test), 92 (internet test)
-IELTS: 6.5, where no part has a score lower than 5.5
-CAE/CPE: Grade A or B

  • Preferably the names and contact details of at least 2 references

If you wish to apply for the position, please apply electronically by clicking the button. We only consider applications submitted through our electronic recruitment system, and all documents must be uploaded in order for your application to be considered. The documents must be in a Scandinavian language or English. Translations must be government authorised, and you may be asked to present originals if you are invited for an interview. OsloMet checks documents in order to give candidates a proper evaluation and ensure fair competition. Incomplete applications will not be considered.

We can offer you

  • an exciting job opportunity at Norway’s third largest and most urban university
  • opportunity to be a part of a dynamic professional environment and unique academic network
  • beneficial pension arrangements with the Norwegian State Pension Fund
  • good employee welfare arrangements and a wide range of sports and cultural offers
  • working location in downtown Oslo with multiple cultural offers
  • an inclusive and friendly work environment
  • norwegian language course
  • on-boarding assistance and other services

The website Living and working in Oslo gives information on living and working in Oslo.

Remuneration

The salary for the position is in accordance with the Basic Collective Agreement for state employees and OsloMet’s pay policy for position code 1017 (research fellow), salary grade 54, i.e. an initial annual salary of NOK 491 100.

By law 2% of the salary is deducted as to the Norwegian State Pension Fund.

According to the Norwegian Freedom of Information Act (Offentleglova) your name may be published on the public applicant list even if you have requested non-disclosure. You will in this case be contacted before your name is published.

Further information

For more information about the position, please contact:

Deadline for applications: 26th of October 2021
Ref: 21/10446

Type of employment Stipendiat
Contract type Full time
First day of employment 1st of December 2021
Salary NOK 491 100 (starting salary)
Number of positions 1
Full-time equivalent 100 %
City Oslo
County Oslo
Country Norway
Reference number 21/10446
Contact
  • Margreth Grotle, 67236043
  • Kåre Rønn Richardsen, 67236626
Published 06.Oct.2021
Last application date 14.Oct.2021 11:59 PM CEST

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