Are you fascinated by the complexity of living cells’ interior? Do you enjoy playing with models of proteins and other biomolecules in the computer? Would you like to use the tools of physics, chemistry, and mathematics to describe processes in cells?

We are a recently founded research group focusing on the multi-scale computer simulation of the cell interior. In particular, we look into how the local structure and dynamics of the intracellular environment can control metabolic processes. Our research is supported by the prestigious Lumina Quaeruntur Award as well as by a grant from the Czech Science Foundation.

Our group is based at J. Heyrovský Institute of Physical Chemistry in Prague, Czech Republic. The group is integrated into the young and interdisciplinary Department of Computational Chemistry, connecting the physical chemistry and biophysics of proteins and membranes with theoretical enzymology and spectroscopy. 

Interested in joining our team? See below for currently available positions. There will also be a postdoc opening available soon. Don’t hesitate to contact us for more information.


Fully funded PhD positions in computational biophysics and biomolecular modeling

We are looking for highly motivated PhD students in computational biophysics / physical chemistry / biomolecular modeling to work on the projects listed below.

PhD project 1: Effect of intracellular environment on enzyme function

Metabolic reactions take place in a highly crowded cellular interior, which is filled with proteins, nucleic acids, metabolites, and other biological molecules. How interactions with such a dense and heterogeneous environment influence—and potentially control—enzyme activity, has not been fully elucidated yet. Understanding these effects would benefit from detailed atomistic insights provided by molecular simulations. The goal of this PhD work will be to link the composition and structure of the local environment around an enzyme to key factors determining enzyme activity, such as the conformational state of the enzyme molecule and binding preferences of its substrates. To reach this goal, the PhD student will establish a computational protocol combining enhanced-sampling molecular simulations with machine-learning approaches. He/she will apply the protocol to systems of growing complexity, ranging from experimentally thoroughly-characterized model systems to complex models of biomolecular condensates involving intrinsically disordered proteins and/or RNA. The results of the work will form an important building block of a multi-scale description of dynamic enzyme assemblies and their role in the regulation of cellular metabolism.

PhD project 2: Computational modeling of dynamic enzyme assemblies

In living cells, various enzymes have been found to assemble into transient structures that can appear and disassemble as a function of external conditions. Among other examples, such dynamic assemblies have been identified in glycolysis or in the purine synthesis pathway. Recent experimental evidence points to a key role of dynamic enzyme assemblies in the regulation and adaptation of cellular metabolism, including their possible role as a switch between two or more competing pathways. However, the mechanisms underlying the formation and function of these assemblies are yet to be elucidated. By using a combination of atomistic, coarse-grained and ultra-coarse-grained molecular modeling and working in tight connection with experimental data, the PhD student will characterize molecular interactions promoting assembly formation and quantify the diffusivities of enzymes and reactants inside dynamic enzyme assemblies. In particular, he/she will evaluate the potential for substrate channeling, that is, passing the intermediate products efficiently between consecutive enzymes of a pathway. The computational methodology developed in this work will serve as a basis for the prediction of metabolic fluxes given a composition and architecture of an enzyme assembly.

PhD project 3: Mechanisms of allostery and regulation in glycolysis

Glycolysis is a key metabolic pathway, forming a starting point of several other important pathways. As such, it is subjected to extensive regulation allowing it to respond to the cell’s varying demands of energy and building blocks. However, molecular details of this complex regulation are still not fully understood. In this work, the PhD student will use a variety of computational approaches, including molecular dynamics simulations coupled with enhanced-sampling techniques, to elucidate the mechanisms of allosteric regulation of glycolysis by cellular energy signals. A focus of the work will be on PFK1, a rate-limiting enzyme forming a “gatekeeper” of glycolysis. The work will benefit from the currently expanding set of available structural data of glycolytic enzymes, including data obtained by our experimental collaborators.

Starting date

Summer 2023 (no later than October 1)


The candidates are expected to hold a MSc (or an equivalent) in physics, chemistry, or related fields before the start of the position. They should be interested in biomolecules and motivated to learn new things. Moreover, they should possess good computer skills and be fluent in English. Experience with molecular simulations and programming would be a plus. The successful candidates will enroll at Charles University in Prague, the top-ranking university in the Czech Republic.

How to apply

If you are interested, please send us your CV together with your motivation letter, transcripts of all courses and grades, and two contacts as a reference to Please indicate in your application which of the three PhD projects listed above you would be primarily interested in. Please write in the subject line of your email SC2023_04. If you have any questions, contact

Application deadline

March 20, 2023

Here is the link to the official advertisement by Heyrovský Institute.