University of Greifswald Institute of Microbiology

Department: Bacterial Physiology

Leibniz Institute for Plasma Science and Technology (INP) Greifswald

Departments: Plasma Bioengineering und Data Science Methods

Your tasks

• In this thesis you will first study microbiological growth modelling in general based on established standard models.
• You will then examine the different theoretical meanings of the various models.
• Next simulation studies (e.g. Monte Carlo simulations) will be used to determine the agreement of existing laboratory data with the models.
• Afterwards you will test model extensions/changes to represent the influences of plasma treatments.
• The aim of the thesis is to create an adapted growth model that formally describes the possible effects of plasma-driven decontamination and brings them into accordance with existing laboratory data. This model should subsequently serve as the basis for industrially relevant applications.

Your profile

• You are interested in how laboratory and simulation data relate to each other.
• You have basic knowledge in biology and programming (e.g. Python).
• Ideally you have had prior exposure to biological growth models microbiological studies or simulation of biological processes.
• The ability to work independently is an advantage.
• Good English and/or German skills are required.

Your benefits

• You will gain insights into applied research outside of the university environment.
• You will have the opportunity to collaborate with colleagues from different disciplines.
• Contributing and implementing your own ideas is encouraged.

We value and promote the diversity of skills of our employees and therefore welcome all applications regardless of age gender nationality ethnic or social origin religion beliefs disability as well as sexual orientation and identity. Severely disabled persons will be given preferential consideration for employment if equally qualified.

Data Science Methods

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