PhD Student 80-100 %
Surgical Outcome Research Center
We are looking for a motivated PhD Student who will contribute to our mission of improving surgical outcomes and support the development of innovative approaches in evidence-based decision-making in surgical outcomes. The PhD Student's main objective is to coordinate and implement the investigation bridging the knowledge and interpretation gap between the various stakeholders by developing an evidence-based, transparent, and standardized approach for the definition and classification of etiology of rotator cuff tears. The doctoral student will further discriminate between traumatic and degenerative cases using predictive modeling techniques and incorporate the potential of multimodal data using nationwide imaging and clinical data, to reduce uncertainty and support a transparent decision-making. The PhD Student will be given the unique opportunity to apply and expand her/his skills, particularly in clinical epidemiology, biostatistics and study management. The project will be conducted under the direction and supervision of Prof. Andreas Marc Müller (Chefarzt, Orthopädie und Traumatologie) and postdoctoral researcher Stéphanie Giezendanner at the Surgical Outcome Research Center (SORC), headed by Prof. Laurent Audigé.
What you will be doing
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)
Your profile
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
Please follow the link to apply: https://jobs.unispital-basel.ch/job-invite/27210/
