Student projects


We warmly welcome students wishing to pursue a Bachelor or Master thesis project, as well as student projects and student assistantships. We offer a wide variety of topics and methods with a focus on the interface between theoretical and experimental biology. Find out more about current projects and join us! Open student projects are listed below, when available. If there are no offers listed, please feel free to send a research proposal.


  • Central carbon metabolism in cancer cells

    In this project we want to design optimal experiments (C13) to build a detailed kinetic model of the central carbon metabolism in cancer cells. 

    The first step would be to build a small model of glycolysis and use artificial data to investigate the possibilities to find parameter values in this model (parameter identifiability). The model can be extended with additional pathways, e.g. TCA cycle, different kinetic descriptions (mass action kinetics, Michaelis-Menten kinetics or convenience kinetics), or different nutrient conditions, e.g. glucose limitation.

    The created model is using ordinary differential equations (ODEs), a specific tool or language for the implementation is not predetermined, although the use of R is recommended. Programming skills or knowledge in dMod is not mandatory.

    In this project you will learn more about the central carbon metabolism and the metabolism of cancer cells in general, expermental design principles, the implementation of dynamic mathematical models, and the concepts of non-linear optimisation.

    If you're interested in this project please contact Roman Rainer.

  • Yeast cell cycle model parametrization

    One of the main challenges in systems biology is to identify model parameters to make useful model predictions. At the same time, parameter estimation is difficult due to complex model structures and limited data availability. Typically, parameters are estimated with non-linear optimization methods. These methods are classified in local and global optimizers.

    The aim of the project is to investigate the performance differences of local and global optimizers for model parametrization related to the yeast cell cycle.

    The starting point will be to familiarize oneself with the theoretical background of non-linear optimization. The next step is to use a toy model and generated data to learn optimization in practice. There are some useful software tools available to solve optimization problems: D2D or dMod (local) and AMIGO or GA (global) for MATLAB and R respectively. Finally, the toy model should be extended to a realistic model describing the time evolution of the key players for the G1 to S phase transition over the cell cycle.

    The model system is using ODEs. R is the recommended programming language. Using the software tools is not mandatory but still helpful to write your own scripts.


    If you're interested please contact Julia Katharina Schlichting.

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