We are always interested in hearing from talented and enthousiastic individuals whose research interests align with the lab’s. Please send a CV, cover letter, and contact information for three references to Prof. Heinemann.

Candidates should have conducted master (or PhD) research in (molecular/systems/synthetic) biology, biochemistry, biophysics, biochemical engineering, or a closely related field.

Currently open positions for PhD students and postdocs

2 positions (PhD student or postdoc) in research line “how metabolism controls the eukaryotic cell cycle”

Proper cell growth and division is crucial for all forms of life. We have recently uncovered that next to the well-known cyclin-dependent kinase system, metabolic oscillations have a crucial role in cell cycle control (Papagiannakis et al, 2017, Molecular Cell; Litsios et al 2019, Nature Cell Biology). However, it is not known yet how metabolism performs this cell cycle control. This is what we would like to find out. Exploring on how an intrinsically dynamic cellular metabolism controls the process of cell growth and division is not only a great scientific adventure, but also harbors significant potential for medical relevance, as compromised cell cycle control has been attributed to several diseases, such as cancer.

In position 1, we will use budding yeast as a model and latest state-of-the-art fluorescence time-lapse microscopy and microfluidics as a key tool to uncover how metabolism performs this important function. Fluorescent reporter constructs will allow us to retrieve cell cycle-resolved information, and optogenetic tools and tools for inducible protein depletion will allow us to perturb the system dynamically and even with single-cell resolution. With combining in a clever manner knowledge from the literature, the insights from the dynamic observations during the cell cycle, and the targeted dynamic perturbations, we will be able to derive testable hypotheses on how metabolic cell cycle control is exerted. Fluorescence microscopy, image analysis and molecular biology/genetics (i.e. to generate the reporter and perturbation constructs) will be important tools in this project. Yet, no prior experience in these tools are required. The reason for this is that we are convinced that excellent candidates with the right motivation can learn everything. Thus, if you find the topic of this project interesting, but you do not have any experience in these tools, do not hesitate to apply.

In position 2, we will use latest state-of-the-art omics techniques to uncover how metabolism performs this important function. Here, we will focus on proteomics, on mapping of posttranslational modifications and on genome-wide analyses of structural changes of proteins and RNA, using latest state of the art techniques. Advanced statistical methods and network-based computational analyses of the generated cell-cycle-resolved data will allow us to generate testable hypotheses on how metabolic cell cycle control is exerted. This project has an experimental component (i.e. omics analyses, done partly together with collaborators) and a computational component (i.e. analyses of the generated data). No prior experience in experimental analyses is required, as there is sufficient expertise present in the lab and with the collaborators, offering an opportunity to learn these techniques. A formal education in computer science, engineering, bioinformatics, or in biology with some experience in computational analyses (e.g. Python) would, however, be helpful as the main challenge here in this project will be the clever analyses of the generated data, such that new insights can be retrieved.

1 position (PhD student or postdoc) in research line “how metabolism functions”

The lab has recently found that cellular metabolism does not operate beyond a certain Gibbs energy dissipation rate (Niebel et al. 2019, Nature Metabolism). This thermodynamic limit could explain the type of metabolism that cancer cells show. We are now highly interested to uncover the molecular mechanism that is responsible for this thermodynamic limit. Here, we hypothesize that enzymes during their catalysis get actively displaced in space, inducing increased molecular motion in the cell and mixing up of the cytoplasm. We have described this hypothesis in a recent perspective article (Losa et al, 2022, Molecular Systems Biology).

In this project, we like to explore the above mentioned idea. To this end, we will use the bacterium E. coli as a model and will perform highly sophisticated microscopy experiments with different dynamic particle tracking technique to measure diffusion rates in cells. Furthermore, in model-based experimental analyses, we aim to determine the Gibbs energy dissipation rates under different metabolic conditions. This project has a focus on biophysical experiments (e.g. single-particle tracking microscopy). No specific prior experience in these experimental techniques is required, as there is sufficient expertise present in the lab, offering an opportunity to learn these techniques.

Exploring how an active metabolism as an out-of-equilibrium system induces intracellular motion is not only a great scientific adventure with the potential to open up a new avenue how dynamic cellular metabolism might control cellular processes (i.e. through motion), but it also harbors significant potential for medicine and biotechnology, where metabolism plays a key role.


Candidates should send their application to Prof. Matthias Heinemann (m.heinemann@rug.nl). The application should contain (i) a CV, (ii) information about grades and other measures of success, (iii) two letters of recommendation (these can also be emailed directly), or names of potential references, and (iv) a short statement on how the candidate’s prior experience/expertise could be connected to one of the above mentioned projects.

(Under-)graduate Students

We are always actively looking for Master student researchers to join the lab. Please email Dr. Heinemann for more information.