Postdoctoral Research Fellow / Senior Scientist (focus: mathematical modelling of healthcare-associated infections) (gn*)
Ref. 04552
Full-Time
Salary according to TV-L E13

(*gn= gender neutral)

The Clinical Epidemiology Unit uses and develops modern statistical and mathematical methods for the analysis of primary and secondary data. A particular focus of the Unit is the application of dynamic mathematical modelling approaches in order to simulate the spread of infectious agents in human populations.

The position:
-Will lead the modelling work in a third-party funded project on the effects of architectural and structural interventions for the spread of healthcare-associated infections in hospital wards (InnoBRI funded by the Innovationsausschuss of the Gemeinsame Bundesausschuss)
-Involves the design and analysis of an agent-based mathematical model mirroring the structure and architecture of a typical German hospital ward
-Will collaborate closely with microbiologists, architects and health economists
-Will add key evidence to an important and up-to-date research topic
-Is planned to result in publications in high-quality peer-reviewed international journals

What we expect:
-Master’s degree and (preferably) PhD e.g. in Biostatistics, Epidemiology, Mathematics or Physics
-Experience in mathematical modelling and simulation studies
-Expert knowledge in statistical programming (e.g. R, Python, C++)
-Analytical and structured way of working, good team and communication skills, as well as a sense of responsibility and quality awareness
-Excellent English or German language skills

What we offer:
-Support with (and access to all prerequisites necessary for) obtaining a postdoctoral lecture qualification (Habilitation)
-Support for further personal training not directly related to the project (e.g. structured development of leadership competencies)
-An interesting and versatile project with challenging tasks
-Training and work in a multidisciplinary and committed research team

If you have any questions about the position, please contact Prof. Dr. André Karch (akarch@uni-muenster.de).

Please send your application including a CV and a letter describing your motivation to work with us until 25.03.2020 to Personalgewinnung des Universitätsklinikums Münster, Bewerbermanagement, Domagkstraße 5, 48149 Münster or via e-mail to Bewerbung(at)­ukmuenster(dot)­de.

Applications of women are specifically invited. In the case of similar qualifications, competence, and specific achievements, women will be considered on preferential terms within the framework of the legal possibilities. Handicapped candidates with equivalent qualifications will be given preference.