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Project description

Herpesviruses are prevalent pathogens in humans and responsible for diseases ranging from relatively harmless cold sores to cancer. They utilize a broad range of mechanisms to modulate their host cells and evade the immune system. To study these mechanisms in an unbiased and system-wide manner, we utilize a systems biology approach to measure various parameters on molecular level in a quantitative manner.

For many techniques such as RNA-seq or quantitative tandem mass spectrometry, computational analysis tools are widely established. However, novel computational and statistical approaches are required for variations or modifications of such experiments and integrative analyses.

We focus on two herpesviruses with distinct modes of host interaction, herpes simplex virus 1 (HSV-1) and murine cytomegalovirus (MCMV). For both viruses, several big data sets (4sU-seq, Ribo-seq, MS/MS, ATAC-seq, PAR-CLIP, ChIP-seq, mNET-seq, …) are either already available or will be obtained in collaboration with Prof. Lars Dölken (Institute for Virology and Immunobiology, University of Würzburg).

The goals of this research project are (i) to develop new computational and statistical methods for the raw data analysis of high-throughput experiments, (ii) to implement software pipelines for the application of these and other established methods to the herpesvirus data, (iii) to characterize and compare the mechanisms of herpesvirus-host interaction and (iv) to develop and apply tools for the integrative analysis of many high-throughput experiments and publicly available data.


Ideal candidates have a strong background in programming, statistics and bioinformatics. Applicants should hold a master’s degree in bioinformatics, computer science, statistics, biology or related fields.

How to apply

The application should comprise a letter of motivation to pursue a PhD, CV including certificates and contact details of 2-3 references. Please send the application via email to Prof. Florian Erhard, Institute for Virology and Immunobiology, University Würzburg.