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PostDoc in Network Epigenomics

Technical University Of Munich
TUM School of Life Sciences Weihenstephan, Chair of Experimental Bioinformatics, Group of Big Data in BioMedicine
Germany Bavaria Freising
https://biomedical-big-data.de/post/job-announcement-nov18/

Description

Full time position for a PostDoc to fill in the newly established group for Big Data in Biomedicine at the Chair of Experimental Bioinformatics, Technical University of Munich, Freising, Germany.

Project description:
A major research barrier in systems biomedicine is that most of the currently used gene-gene interaction networks are not cell type-specific and neglect much of our current understanding of cellular regulation (i.e. enhancers and repressors). The EpiMap project of the International Human Epigenome Consortium currently integrates and harmonizes multi-omics data from 1000 epigenomes, offering a unique chance to overcome this barrier. The aim of this research project is to use state-of-the-art machine learning techniques for multitask and transfer learning to construct robust cell-type-specific molecular interaction networks. Such networks will allow researchers to put their experimental results in a cell type-specific context and thus pave the way towards adding an epigenetic perspective to biomedical research in general and to systems medicine in particular.

What we offer:
At the Chair of Experimental Bioinformatics you will find a supportive and productive research environment with a young, dynamic team of more than 20 international researchers at different stages in their career and education. Find us online at: https://www.exbio.de and https://biomedical-big-data.de.

The position is available starting immediately and initially limited for 3 year with a gross salary calculated according to A13 TV-L.


Qualifications

- Recent PhD in Computational Biology, Bioinformatics, Genomics, Epigenetics or a related field.
- Strong experience with handling RNA-seq, small RNA-seq, WGBS, RRBS, ChiP-seq data
- Strong experience with systems biology and network analysis techniques
- Strong experience with advanced machine learning techniques, e.g. SVNs, RF, CNN
- Strong experience in R, Python or Java
- Good experience in using compute clusters / HPC environments and Docker / Singularity
- Solid understanding of molecular biology in general and epigenetic mechanisms in particular
- Ability to independently carry out a challenging research project in an international collaboration
- Fluency in English in written and spoken language.


Start date

As soon as possible

How to Apply

Interested? Send your application including your CV, the most relevant publications and two reference letters to markus.list@wzw.tum.de.


Contact

Markus List
markus.list@wzw.tum.de