|Staff Category:||Postdoctoral Fellow|
|Contract Duration:||3 years|
|Closing Date:||18 March 2018|
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 combines 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 fellow will develop new statistical methods for interrogating single-cell RNA-seq and other single-cell variation datasets. The project is closely connected with the Human Cell Atlas, to which the Stegle group contributes as a node in the analysis working group. We aim to derive advanced statistical methods that scale to datasets with millions of cells, combining 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 expertise and methods devised by the Stegle, including factor model, linear mixed models and methods based on deep learning (see below). The position will be primarily based at EMBL Heidelberg but regular exchange and visits to the Genome Campus in Hinxton are facilitated by the dual location of the team.
• 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.
• Buettner, F., et al. (2017) f-scLVM: scalable and versatile factor analysis for single-cell RNA-seq." Genome biology 18.1 (2017): 212.
• Argelaguet, R., et al. (2017). Multi-Omics factor analysis disentangles heterogeneity in blood cancer. bioRxiv, 217554.
• Svensson, V., et al. (2017). SpatialDE-Identification of spatially variable genes. bioRxiv, 143321.
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.
Qualifications and Experience
The successful applicant will hold 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. (S)he 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.
Please apply online through www.embl.org/jobs.
Informal enquires should be direct to email@example.com.
EMBL is an inclusive, equal opportunity employer offering attractive conditions and benefits appropriate to an international research organisation with a very collegial and family friendly working environment. The remuneration package comprise a competitive salary, a comprehensive pension scheme, medical, educational and other social benefits, as well as financial support for relocation and installation, including your family.
Please note that appointments on fixed term contracts can be renewed, depending on circumstances at the time of the review.