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Postdoc (f/m/d) Computational Biology
Published(52 days ago)
Deutsches Krebsforschungszentrum / German Cancer Research Center (DKFZ)Heidelberg
The German Cancer Research Center is the largest biomedical research institution in Germany. With more than 3,000 employees, we operate an extensive scientific program in the field of cancer research.
The Division of Computational Genomics and System Genetics is seeking a
A postdoctoral position in computational single-cell genomics is available in the Computational Genomics and Systems Genetics group (https://www.dkfz.de/en/bioinformatik-genomik-systemgenetik) at our laboratory at the German Cancer Research Center in Heidelberg, Germany.
Our group is relocating from Cambridge to Heidelberg, where we are based both at DKFZ and EMBL Heidelberg (https://www.embl.de/research/units/genome_biology/stegle/). Postdoctoral positions are available in the field of single-cell genetics. We seek to develop and apply computational approaches for integrating genetic factors with single-cell readouts in the context of oncology and human variation. This project will be embedded in the context of a recently funded Human Cell Atlas project (https://www.humancellatlas.org) that seeks to perform large-scale human genetic variation analysis at the single-cell level in organoids and primary tissues. Postdoc positions can either be focused on statistical methods development, computational analysis workflows or visualization work benches.
The fellow will be located in the Stegle group and collaborate with partners in the Human Cell Atlas, collaborators in Heidelberg, Vienna, Cambridge and elsewhere. We seek to build on previous expertise and methods devised by our team (see below). The position will be primarily based at DKFZ Heidelberg but is connected to our activities at EMBL Heidelberg and the Genome Campus in Cambridge.
Recent relevant publications:
Cuomo, Anna SE, et al. "Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression." BioRxiv (2019): 630996.
McCarthy, Davis James, et al. "Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants." bioRxiv (2018): 413047
Argelaguet, R., et al. (2018). Multi-Omics Factor Analysis—a framework for unsupervised integration of multi-omics data sets. Molecular Systems biology, 14, e8124.
Svensson, V., et al. (2018) SpatialDE: Identification of spatially variable genes. Nature Methods, 343–346.
Buettner, F., et al. (2015). Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nature biotechnology, 33(2), 155.
The successful applicant will hold a master as well as a doctoral degree or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical development.
Previous experience in developing and applying computational methods applied to large datasets is expected. Expertise in analysis and integration of multiomics data, statistical genetics, statistical interpretation and analysis of next-generation sequencing datasets is beneficial, as is communicating results in scientific conferences and papers.
We especially seek candidates with prior experience in developing statistical methodology in a genomics context, including gene expression analysis, factor models, GWAS and analysis of NGS data. A good foundation in, and previous usage of methods in any of the following fields is advantageous: statistics, machine learning, genetics, optimization and mathematical modeling. A background in molecular biology, or previous experience tackling biological questions is beneficial but not necessary.
Proficiency with a high-level programming language (e. g., C++, Java) and/or appropriate scripting languages, and statistical data analysis tools such as R, MATLAB or Python is required.
The ideal applicant should have demonstrated the ability to work independently and creatively. You should have excellent communications skills and be able to articulate clearly the scientific and technical needs, set clear goals and work within an interdisciplinary setting, communicating with other partners within the Human Cell Atlas project.
The position is limited to 2 years.
The position can in principle be part-time.
For further information please contact
Dr. Oliver Stegle, phone +49 6221 42-3598.
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.
To apply for a position please use our online application portal
We ask for your understanding that we cannot return application documents that are sent to us by post (Deutsches Krebsforschungszentrum, Personalabteilung, Im Neuenheimer Feld 280, 69120 Heidelberg) and that we do not accept applications submitted via email. We apologize for any inconvenience this may cause.
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