We can host students with different backgrounds and have diverse projects for different interests. We often co-supervised students with other groups from the CNB who want to work closely with experimental data. It is also possible that you come up with your own project that you want to pursue. In any case, contact Florian (f.m.berger@uu.nl) to setup an orientation meeting. We have some interesting projects:

Machine-learning model discovery for oscillations of hair bundles.

In this project, you will dive into recent developments in machine learning to describe the non-linear oscillations of hair bundles. Such computational approaches, based on ODE reconstruction and neural differential equations could complement previous mathematical models and are promising to discover new aspects of these dynamics.

For this project, you should be enthusiastic about ML, programming, non-linear stochastic systems, and of course hair cells (the most beautiful cells, according to Florian’s opinion)

Fluctuation theorems for intracellular cargo transport

Intracellular cargo transport is important for every cell to maintain its organization. In recent years, novel relations have been discovered that are applicable in a wide context of non-equilibrium systems. By combining these results with simulated data, we will explore how relevant they are to analyzing real experimental data.  

For this project, you should be enthusiastic about nonequilibrium thermodynamics, cargo transport by molecular motors, programming, and stochastic physics.

Microtubule length regulation by Kif21b

By using agent-based simulations with cytosim, we will explore the length regulation of microtubules by Kif21b and focus especially on the shape of the cell and boundary effects. What is the best mechanism to tightly regulate the length of microtubules with motor proteins?

For this project, you should be enthusiastic about computer simulations and motor proteins with their cytoskeleton.

Optogenetics and control theory

With optogenetics, it is possible to control the activity of molecules in space in time, but a rigorous theoretical integration of such experiments is missing. We have several lines of research in this direction, concerning light-induced gliding assays, repositioning of organelles, nuclear export, and controlled cell motility.    

For these projects, you should be enthusiastic about optogenetics and control theory

Machine learning for analyzing molecular motors and microtubules

Often piecewise-linear descriptions are used to describe the dynamics of microtubules and motor proteins in cells. It is far from obvious how to calibrate these models best to experimental data. We will use new methods to systematically investigate how this kind of data can be best analyzed.

For this project, you should be enthusiastic about statistical models, programming, and intracellular dynamics.

Response functions to study the activity of hair cells

Response functions provide many interesting aspects of equilibrium and nonequilibrium systems. In this project, we will use computational approaches to determine the response function for different models of hair cell activity and relate the results to the dissipated energy. 

For this project, you should be enthusiastic about non-equilibrium thermodynamics, computer simulations, and hair cells.