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Postdoctoral Scientist for Computational Genomics and Epigenomics : Heidelberg, Germany

The German Cancer Research Center is the largest biomedical research institution in Germany. With more than 2,700 employees, we operate an extensive scientific program in the field of cancer research.

The Division of Pediatric Neurooncology is seeking a
Postdoctoral Scientist 
for Computational Genomics 
and Epigenomics 
(Ref-No. 208/2015)

Description:
This position will involve working in the Division of Pediatric Neurooncology (headed by Prof. Stefan Pfister, at the German Cancer Research Center (DKFZ), Germany's largest biomedical research institute. The candidate will be part of the Computational Oncoepigenomics group headed by Dr. Lukas Chavez, which is embedded in the Division of Pediatric Neurooncology. The team is very international and multidisciplinary, and the working atmosphere is lively and friendly, working language is English.

Through various large genome and epigenome sequencing projects, the division has existing unprecedented datasets to be further analyzed and used for the establishment of new bioinformatics tools. The Computational Oncoepigenomics group aims to comprehensively understand the genetic and epigenetic diversity of childhood brain tumors by developing and applying bioinformatics methods for the analysis of large-scale biological data. We analyze tumorous and non-tumorous tissue by next-generation sequencing including genome, transcriptome, methylome, and histone ChIP sequencing. All of these analyses generate a tremendous amount of data that serves as a unique resource for sophisticated modeling, visualization, and interpretation by computer-assisted methods. Specific research interests include (but are not limited to):

Comparative enhancer mapping between different types of pediatric brain tumors

Characterization of histone modification states across pediatric brain tumors

Analysis of genomic structural variants and their effects on enhancer activity and gene expression

Modeling of RNA sequencing data to identify novel mutations and gene fusions

Integration of different levels of genomic and epigenomic data

Identification of drug targets and drug matching for recurrent malignant childhood brain tumors based on high dimensional biological data to improve treatment decisions

 

Our group has solid experiences in developing bioinformatics tools for high-throughput sequencing data analysis and we routinely apply our and other bioinformatics tools in the context of large-scale DNAmodification and enhancer mapping studies in health and disease.

Your profile:
The position will involve participating in groundbreaking pediatric brain cancer sequencing projects within the International Cancer Genome Consortium (ICGC), amongst others. As such, applicants must be highly talented and motivated to work independently and to a high standard within a demanding but highly rewarding framework. The candidate should have experience in analyzing short read DNA sequencing data ideally in the context of transcriptomes and epigenomes (i.e. DNA methylation, histone modifications, DNA-protein interactions). Demonstrable skills in programming and biostatistics (e.g. Perl, Python, R, Matlab, machine learning) as well as the Unix computing environment (e.g. BASH, HPC usage) are essential. The applicant should hold a Ph.D. in bioinformatics or a related field. Candidates with a background in computer science, mathematics or statistics should be familiar with molecular biological methods.

The application should include a cover letter, curriculum vitae, copies of relevant degree certificates, and contact details for at least two references.

The position is limited to 2 years. The position can in principle be part-time.

For further information please contact
Dr. Lukas Chavez, phone 06221 42-4676.

The German Cancer Research Center is committed to increase the percentage of female scientists and encourages female applicants to apply. Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.

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