PhD Student 80-100%
Surgical Outcome Research Center
What you can move
* Contribute to a research project aiming to bridge interpretation gaps between clinicians, health insurers and patients by developing evidence-based approaches for defining and classifying rotator cuff tear etiology
* Perform a systematic literature review and Delphi survey to establish a consensus definition for rotator cuff tear etiology, and to define and weight a list of diagnostic factors for distinguishing between traumatic and degenerative rotator cuff tears (WP1)
* Identify eligible patients as part of the Swiss National Science Foundation ARCR_Pred study and conduct a retrospective analysis evaluating the discrimination performance of the factors identified in WP1, with the aim of developing and assessing an innovative diagnostic tool to support clinical decision-making (WP2)
* Contribute to the design and development of a protocol for a prospective study to externally evaluate the diagnostic tool in a primary care setting (WP3)
You should bring
* MSc/MA in a health-related field such as Medicine, Physiology, Biology, Biomedical Engineering, Epidemiology, Biostatistics, Data Science or Computational Science
* Experience in at least one of the following areas: diagnostic and prognostic research, Delphi surveys, evidence-based decision-making, surgical outcomes, advanced statistical modelling, or machine learning methods for outcome prediction or automated image analysis
* Programming skills in R or Python
* Strong project management, analytical and communication skills
* Fluency in English (spoken and written) and German (B1 level required); knowledge of French or Italian is an asset
Benefits of this position
* International, interdisciplinary and dynamic working environment
* Opportunity to develop your personal research portfolio within the framework of the funded research proposal
For more informations about the position, please contact the following person: Beate Hartmann, Head of Research Management SORC-B, under phone number
Dagmar Angelika Bildl, Human Resources, would be pleased to receive your complete application online. (Code number
Universitätsspital Basel
Rekrutierung
www.unispital-