UKM Universitätsklinikum Münster | Germany | 48xxx Münster | Student job | Part time - flexible | Published since: 14.11.2025 on stepstone.de
Student Assistant (gn*) Anesthesiology
Student Assistant (gn*) Anaesthesiology Limited to 1 year | Part-time with 7 hours a week | Clinic for anaesthesiology, surgical intensive care and pain therapy | We're the UKM. We have a clear social mission and special responsibility with the connection of medical care, research and teaching. During your work alongside your studies in the field of human medicine, you benefit from individual care, attractive framework conditions and many ways to grow and introduce yourself. Together we want to successfully start the future – best with DIR! Within the framework of the IMF-funded pilot project "Process Mining in Cardiopulmonary Resuscitation", two student assistants (SHK) are sought, which support our interdisciplinary team in researching workflows during Advanced Life Support (ALS) in simulation scenarios. The aim of the project is to identify process deviations by means of process mining and to evaluate their influence on the reanimation quality. A central component is the implementation of standardised reanimation scenarios in the UKM training centre over a period of 12 months. .
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Your tasks • Your profile • What we offer
Student Assistant (gn*) Anaesthesiology Limited to 1 year | Part-time with 7 hours a week | Clinic for anaesthesiology, surgical intensive care and pain therapy | We're the UKM. We have a clear social mission and special responsibility with the connection of medical care, research and teaching. During your work alongside your studies in the field of human medicine, you benefit from individual care, attractive framework conditions and many ways to grow and introduce yourself. Together we want to successfully start the future – best with DIR! As part of the IMF-funded pilot project “Process Mining in Cardiopulmonary Resuscitation” two student assistants (SHK) are being sought, which support our interdisciplinary team in researching workflows during Advanced Life Support (ALS) in simulation scenarios. The aim of the project is to identify process deviations by means of process mining and to evaluate their influence on the reanimation quality. A central component is the implementation of standardised reanimation scenarios in the UKM training centre over a period of 12 months.
Participation in the implementation of standardised reanimation scenarios in the UKM training centre over a period of 12 months Extraction and processing of event logs from Laerdal LLEAP software to capture simulation data Manual video annotation and addition of time stamps for events that are not automatically detected Ensuring standardized processes during simulations to ensure data quality Cooperation with an interdisciplinary team of experienced intensive care professionals
Immatrikulation in the course of human medicine, preferably in the clinical section Interest in emergency medicine, data analysis and medical research Reliability, teamability and structured operation Pre-experience in rescue or simulation training is advantageous, but not absolutely necessary
An exciting activity in an innovative research project with direct reference to emergency medicine Flexible working hours that can be agreed with the study Insights into Modern Research Methods in Process Mining and Simulation Medicine Care and mentoring by experienced clinicians Possibility of co-authorship in scientific publications CONDITIONS: Varied Flexible working hours Relevant professional experience Attractive remuneration Further advantages
Company location
Location
| UKM Universitätsklinikum Münster | |
| 48149 Münster | ||
| Germany |
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