I am fascinated by randomness, how it impacts living systems, and the strategies to cope with it and exploit it. How do living systems deal with fluctuations without being overwhelmed by them? How do cells manage to employ their stochastic machinery to process noisy signals and nonetheless perform tasks reliably? How much does this cost them? How can we exploit fluctuations to design efficient microscopic engines?
These are a few of my favourite questions that drive my research at the interface between statistical physics and biology. In investigating them, I make use of tools from stochastic processes, non-equilibrium thermodynamics, stochastic optimal control, information theory, and machine learning. These tools often steal the stage and developing them becomes the focus itself.

Here you can find a video summarising our recent results on the stochastic motion of single molecules in biomolecular condensates.

Open Positions

• PhD position on an exciting project to use statistical physics and machine learning to study force-sensing proteins. The project is interdisciplinary and involves the possibility of doing experiments in the lab of Rafel Tapia-Rojo and developing molecular dynamics simulations under the supervision of Chris Lorenz. The position's start date is October 1st 2024. The first deadline for applying is on April 17th. Later applications may be possible but interviews are taking place on a rolling basis.
  Apply here!
  Informal enquiries are welcome, just email me.

• For postdoc positions please email me to explore funding opportunities.