Job:Postdoc Computational Biology Of Icgc Pan-Cancer Genomes – Integrative Data Analysis , Embl, Heidelberg, Germany
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10.6 years ago
jan.o.korbel ▴ 10
  • Location: Heidelberg, Germany
  • Staff Category: Postdoctoral Fellow
  • Contract Duration: 2 years
  • Grading: N/A
  • Closing Date: 25 August 2013
  • Reference number: HD_00372

Job Description

The European Molecular Biology Laboratory (EMBL) is one of the highest ranked scientific research organisations in the world. The Headquarters Laboratory is located in Heidelberg (Germany) and the outstations are in Grenoble (France), Hamburg (Germany), Hinxton (UK) and Monterotondo (Italy).

Recent advances in massively parallel DNA sequencing technology have facilitated molecular cancer research at unprecedented resolution, through whole cancer genome analyses and data integration approaches building on patient clinical phenotype and polyomic (e.g. transcriptome and epigenome) data. The Korbel group is at the forefront of cancer genomics approach development (example references are below), playing leadership roles in large-scale studies that apply genomics techniques in conjunction with sophisticated data integration approaches to unravel the extent, origin, and phenotypic impact of genetic variations in the germline and in cancer. A current aim of the group is to develop novel computational approaches to enable comparisons of thousands of deeply sequenced cancer genomes in the context of upcoming whole genome pan-cancer studies. For computational biologists, this new area offers exciting opportunities, ranging from the development of computational genomics-driven and statistical algorithms for primary data analysis to data integration and systems-level inference of relevance for the future of precision medicine.

We are looking for a PhD-level computational biologist, physicist or computer scientist who is interested in being actively involved in the design and analysis of large-scale cancer genomic/polyomic data and their integration with clinical phenotypes. He/she will address novel research questions at the intersection of computational genomics and clinical cancer research. In addition to computational office space, the Korbel group has experimental “wet” lab space, whereby intense collaborative interactions between “dry” and “wet” lab researchers are highly encouraged and have in the past been very successful.

Qualifications and Experience

The successful candidate should hold a PhD, and should have carried out PhD research in a computational or quantitative discipline (e.g. computational biology, bioinformatics, physics, computer science, statistics). Prior expertise in the analysis of next-generation sequencing data will be considered as a plus. Strong computational skills and ability to perform multidisciplinary work covering computational biology, bioinformatics, biostatistics, genome analysis and collaborative interactions with other team members is mandatory. Experience in data analysis and familiarity with programming languages (e.g. R, Matlab, Python, Perl), and a strong publication record (which can include academic papers and scientific software) is required. Furthermore, reliability, attention to detail, communication skills, effective time management, motivation to work in a multidisciplinary international environment, and the ability to independently take responsibility over his/her own project will be expected. The successful candidate will benefit from the interdisciplinary science pursued in the Korbel group, and the stimulating interactive and international environment at EMBL.


Korbel JO & Campbell PJ (2013). Criteria for inference of chromothripsis in cancer genomes. Cell 152:1226-36.

Weischenfeldt J, et al. (2013). Integrative genomic analyses reveal an androgen-driven somatic alteration landscape in early-onset prostate cancer. Cancer Cell 23:159-70.

Rausch T, et al. (2012). Genome sequencing of pediatric medulloblastoma links catastrophic DNA rearrangements with TP53 mutations. Cell 148:59-71.

Rausch T, et al. (2012). DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 28:i333-i339.

Mills R, et al. (2011). Mapping copy number variation by population-scale genome sequencing. Nature 470:59-65.

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EMBL is an inclusive, equal opportunity employer offering attractive conditions and benefits appropriate to an international research organisation.

Please note that appointments on fixed term contracts can be renewed, depending on circumstances at the time of the review.

cancer genomics structural-variation genetics • 5.2k views

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