Technical University of Munich (TUM)

Data Scientist

Technical University of Munich (TUM)

Munich, Bavaria, Germany

Analysis of Interactome and Protein Turnover Dynamics Regulating Antiviral Immunity


The pathogenic activity of viruses is to a large extent based on their ability to modulate protein activities in infected cells. In the course of an European Research Council (ERC)-funded (5 years perspective) project (ProDAP) we will study the influence of viruses on the host proteome.


We use state-of-the-art mass spectrometry (MS) and deep sequencing techniques to obtain large-scale data and study how viruses and other pathogens transform the landscape of protein interactions. This data is critical to understand how our organism deals with infecting pathogens. To analyze the MS data we have developed comprehensive bioinformatic pipelines combining the leading approaches for Bayesian statistical modeling, biological data processing and visualization (R, Julia, Stan, Plotly, Sun Grid Engine). Follow up evaluation using phenotypic screens based on an automated live-microscopy platform allow functional interpretation of the analysed data. These data will be considered for systems analysis of virus infections.


Your ultimate mission will be to use the power of bioinformatics to study host-pathogen interactions on a systems level. You are expected to further develop the bioinformatic framework and collaborate with other scientists to generate tools that will be used to analyze primary data. The ultimate aim is to identify novel regulatory mechanisms that are used by the immune system, explain how infection with pathogens cause disease and potentially pinpoint druggable hotspots in the antiviral protein-protein interaction network.


The strength of our lab is the synergy between wet-lab work and data analysis. At each stage of the project you will be working in a close collaboration with wet-lab scientists: from the initial experiment design to the hypothesis validation. Your creativity and critical input will be a key driver in these projects.


Requirements

·      university degree

·      strong coding skills (knowledge of R, Julia or Python is a plus)

·      solid knowledge of statistics

·      biological background and/or wet lab experience are a plus

·      fluent English

·      excellent communication skills and general interest in biology

·      motivation letter, CV and names of the two referees

Conditions

·      vibrant, highly interactive and international research group

·      high-profile ERC-funded project

·      one of the most comfortable cities in the world

·      Work contract based on TVÖD/L considering previous experience

 

Please send your application details best before May 1st to either:

Prof. Andreas Pichlmair                     email: andreas.pichlmair@tum.de

Dr. Alexey Stukalov                           email: alexey.stukalov@tum.de

 

Further information can be found at: www.innatelab.org

 

Recent publications of the research group:

Hubel et al., Nature Immunology (2019), Scaturro et al., Nature (2018) PMID: 30177828; Holze et al., Nature Immunology (2018) PMID: 29255269; Haas et al., Plos Path (2018), PMID: 29709033; Gebhardt et al., Nature Comm (2015), PMID: 26382858; Habjan et al., Plos Path (2013), PMID: 24098121; Pichlmair et al., Nature (2012), PMID: 22810585; Pichlmair et al., Nature Immunology (2011), PMID: 21642987; Pichlmair et al., Science (2006), PMID: 17038589

Favorite

Apply with CV and Cover Letter

Must be a .doc, .docx, or .pdf file and no larger than 1MBMust be a .doc, .docx, or .pdf file and no larger than 1MB
Position

Data Scientist