Computational and Single-Cell Epigenomics

We are continuously looking for new people to join our team. At the moment, we have the following open positions:

Bachelor/Master thesis projects in Computational and Single-Cell Epigenomics

We offer a variety of projects ranging from computational tool development, over data analysis, until projects involving wet-lab work. At the moment, we offer the following projects:

• Data analysis tasks around various cancer types using of the RnBeads (rnbeads.org/) toolsuite
• Development of a software tool for the analysis of scTAM-seq data
• Characterizing epigenome heterogeneity in lung cancer
• Predicting chromothripsis from DNA methylation data

Being embedded in the Division of Cancer Epigenomics, we offer a welcoming work atmosphere with a mix of computational and experimental students.

What we are looking for: We are looking for students that are pursuing their Bachelor's and Master's degree at Heidelberg University and that want to do their Bachelor/Master thesis or lab rotation in Computational Epigenomics. Previous experience with programming in R and with epigenomics are advantages.

• Scherer M, Singh I, Braun M, Szu-Tu C, et al. Clonal tracing with somatic epimutations reveals dynamics of blood ageing. Nature 2025. https://doi.org/10.1038/s41586-025-09041-8
• Bianchi, A., Scherer, M., Zaurin, R., Quililan, K., Velten, L., & Beekman, R. (2022). scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells. Genome Biology, 23(1), 229. https://doi.org/10.1186/s13059-022-02796-7
• Scherer, M., Nebel, A., Franke, A., Walter, J., Lengauer, T., Bock, C., Müller, F., & List, M. (2020). Quantitative comparison of within-sample heterogeneity scores for DNA methylation data. Nucleic Acids Research, 48(8), e46–e46. https://doi.org/10.1093/nar/gkaa120
• Müller, F., Scherer, M., Assenov, Y., Lutsik, P., Walter, J., Lengauer, T., & Bock, C. (2019). RnBeads 2.0: comprehensive analysis of DNA methylation data. Genome Biology, 20(1), 55. https://doi.org/10.1186/s13059-019-1664-9
• Scherer, M., Nazarov, P. V., Toth, R., Sahay, S., Kaoma, T., Maurer, V., Vedeneev, N., Plass, C., Lengauer, T., Walter, J., & Lutsik, P. (2020). Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz. Nature Protocols, 15(10), 3240–3263. https://doi.org/10.1038/s41596-020-0369-6

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