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In the last years, single cell and epigenetic characterization techniques have gained tremendous attention in oncology and

broadened our understanding of the diseases. Our group specifically focuses on SMARCB1 deficient pediatric tumors.

To better understand these, we are applying various molecular genetic characterization techniques including ChIPsequencing,

whole genome and exome sequencing and single-cell sequencing.

Recently, we have performed integrative, large-scale multi-omic characterizations of pediatric rhabdoid tumors

(Johann et al. Cancer Cell 2016; Erkek, Johann et al, Cancer Cell 2019) and are now aiming to expand these techniques

to other SMARCB1-deficient tumors. Furthermore, to facilitate the translation of the results back to the clinic, we will

perform high-throughput drug screens which complement the multi-omics characterization of the tumors. To handle

both the experimental and the computational part of this project, we are looking for a highly-motivated PhD student,

who is able to work at the interface of molecular biology, epigenetics and computational biology.


Job description:

We are looking for a motivated PhD student with a background in computational biology (and ideally epigenetics) and an

interest in both wet and dry lab work. Our aim is to decipher the epigenetic landscape of various neoplasias that are characterized

by the loss of the tumor-suppressive SMARCB1 protein, including rhabdoid tumors and epithelioid sarcomas.

The successful applicant will

1) plan and perform drug treatment studies in cell lines of the aforementioned entities

2) apply methods for the epigenetic characterization of these tumors, including methylation analysis,

ChIP-Sequencing and RNA-sequencing

3) perform the integrative analysis of the generated datasets



• Graduation (Master of Science) in biology, cancer biology, genetics, bioinformatics or a related field

(with demonstrated experience in both bioinformatics and experimental work)

• Previous experience in the analysis of array and/or high throughput sequencing data is mandatory

(preferably in R and in a scripting language such as Python)

• Ability to collaborate and communicate within interdisciplinary teams (in German or English)

What we offer:

• Joint appointment at the University of Augsburg (Prof. Dr. M. Schlesner, Computational Biology) and the University

Hospital (PD Dr. P. Johann) and integration into both a clinical / experimental and a computational working group

• The possibility to work on your PhD thesis in a rapidly evolving community

• The opportunity to learn a wide variety of experimental and computational methods

• Support in generating an own, academic profile


Contact: PD Dr. Johann Pascal Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! 

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