The Clinical Epidemiology Unit uses and develops modern statistical and mathematical methods for cutting-edge research questions, especially in the field of infectious disease epidemiology. A major focus of the Unit is the parametrisation of infectious disease transmission models via the collection and extensive analysis of real-world epidemiological data, especially with respect to contact patterns. The Unit is looking for a PhD student for the project “Getting more out of contacts – improved forecasting of disease dynamics by better implementation of contact survey data for parametrisation of infectious disease models” which is funded by the Innovative Medical Research programme of the University of Münster.

The position:

• involves developing a new methodological approach to derive information relevant to disease spread potential from contact surveys, via the use of detailed contact networks parametrised using existing contact survey data
• will add key evidence to a crucial and up-to-date research topic
• includes the collaboration with national and international scientists from various scientific backgrounds
• will lead to high-quality peer-reviewed manuscripts in international journals

What we expect:

• Master’s degree in mathematics, physics or a related discipline
• Experience in infectious disease epidemiology and/or in mathematical modelling would be an advantage
• Good programming skills in relevant programming languages (e.g. Julia, R, Python, C++)
• An analytical and structured way of working, good team and communication skills, as well as a sense of responsibility and quality awareness
• Excellent English language skills; German language skills would be an advantage.

What we offer:

• Full dedication to the PhD project in a semi-structured or unstructured PhD program
• Support for further personal training not directly related to the project (e.g. structured development of leadership competencies)
• An interesting and versatile workplace with challenging and exciting tasks and projects
• Training and work in a multidisciplinary and committed research team