Postdoctoral Fellow - Computational Biology / Genomics

European Molecular Biology Laboratory (EMBL)

Contract Duration: 2 years

Job Description
A Postdoctoral position in computational single-cell genomics is available in the Statistical Genomics and Systems Genetics group at our newly established location as part of the Genome Biology Unit at EMBL Heidelberg in Germany.

Our research group bridges the excellence in genomics and genetics at the Genome Campus in Hinxton, Cambridge, UK with molecular profiling techniques and statistical computing at EMBL Heidelberg, Germany. The postdoctoral fellow will develop and apply novel computational methods for interrogating single-cell RNA-seq and other single-cell variation datasets. The aims of this post are closely connected to the Human Cell Atlas, to which our group contributes as a node in the analysis working group. As a core aim of this project, we seek to develop computational strategies for the joint analysis of datasets with millions of cells, and to integrate spatial technologies with single-cell RNA-seq and epigenome methods. The fellow will be located in the Stegle group and collaborate with partners in the Human Cell Atlas, collaborators at EMBL and elsewhere. We seek to build on previous developments and expertise in the group, including factor model, linear mixed models and deep learning methods (see below). The position will be primarily based at EMBL Heidelberg, however regular exchange and visits to the Genome Campus in Hinxton are facilitated by the dual location of the team. Recent relevant publications:

  • Buettner, F., et al. (2017) f-scLVM: scalable and versatile factor analysis for single-cell RNA-seq." Genome biology 18.1 (2017): 212.
  • Svensson, V., et al. (2018) SpatialDE: Identification of spatially variable genes. Nature Methods, advance online.
  • Angermueller, Christof, et al. (2017) DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning. Genome biology 18.1 (2017): 67.
  • 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.
  • Argelaguet, R., et al. (2017). Multi-Omics factor analysis disentangles heterogeneity in blood cancer. bioRxiv, 217554.

EMBL is Europe’s flagship research organisation for the life sciences – an intergovernmental organisation with more than 80 independent research groups covering the spectrum of molecular biology. EMBL is international, innovative and interdisciplinary – its 1600 employees, from many nations, operate across six sites near Heidelberg, Hamburg, Grenoble, Rome, Cambridge and Barcelona.

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