The Semrau lab
Our lab is interested in the fundamental molecular mechanisms underlying lineage decision-making in stem cells and in vivo. We are fascinated by the question how defined and stable cell types are generated by the interplay of signaling inputs and gene regulatory networks. We study this question by precise quantification of the states of single cells in combination with bioinformatics analysis and machine learning. Based on this quantitative understanding we want to develop new ways to manipulate lineage decisions during in vitro differentiation in precisely controlled ways. Our group is highly interdisciplinary and works at the interface of biology, biophysics, bioinformatics and biomedical sciences.
Semrau, S., van Oudenaarden, A., 2015. Studying Lineage Decision-Making In Vitro: Emerging Concepts and Novel Tools. Annu. Rev. Cell Dev. Biol. 31, 317–345. doi:10.1146/annurev-cellbio-100814-125300
Semrau, S., Goldmann, J., Soumillon, M., Mikkelsen, T.S., Jaenisch, R., van Oudenaarden, A., 2016. Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells. bioRxiv 068288. doi:10.1101/068288
Semrau, S., Crosetto, N., Bienko, M., Boni, M., Bernasconi, P., Chiarle, R., van Oudenaarden, A., 2014. FuseFISH: Robust Detection of Transcribed Gene Fusions in Single Cells. Cell Reports 6, 18–23. doi:10.1016/j.celrep.2013.12.002
Project and key responsibilities
The available postdoc project aims to create a single-cell atlas of the human embryonic kidney. Information about the transcriptional profiles and locations of all cell types in the embryonic kidney will improve our understanding of kidney development and will provide an important benchmark for kidney organoids. In this project you will be responsible for performing single-cell RNA-seq and single-molecule FISH measurements of human embryonic kidney samples. The necessary experimental techniques are established in our lab and samples will be provided by our collaborators. In particular, you will dissociate the tissue and prepare single-cell RNA-seq libraries with the drop-seq technique (Macosko et al., Cell, 2015). You will analyze the RNA-seq data (potentially together with a bioinformatics collaborator) and identify cell types using state-of-the-art machine learning tools. Based on these results you will define a set of marker genes that will allow you to locate cell types by single-molecule FISH in intact tissue sections. This comprehensive spatial molecular data set will then allow you, for example, to establish intercellular signaling networks.
- You hold a PhD degree in one of these disciplines: biology, biochemistry, bioengineering or related disciplines
- You have a strong interest in experimental quantitative biology, in particular related to human development and stem cell differentiation
- You have experience with molecular biology techniques, in particular NGS library preparation
- Experience with programming in R or Matlab and relevant bioinformatics packages is a plus.
- You are proficient in spoken and written English, and have good communication and writing skills
- You are independent, creative and have team spirit
Research at our department
Our lab is part of the Leiden Institute of Physics (http://www.physics.leidenuniv.nl) and situated at the Leiden Cell Observatory (http://cellobservatory.leidenuniv.nl). The Cell Observatory is a highly collaborative community dedicated to the visualization and understanding of the fundamental molecular mechanisms of life, which is part of the core scientific profile of Leiden University. The Cell Observatory houses state-of-the-art bio-imaging facilities shared among the member labs, which actively develop new methods for the quantitative measurement of single-cell properties.
More information about our lab can be found at http://www.semraulab.com/.
Enquiries can be made to Dr. Stefan Semrau (email@example.com).
Information about the Faculty of Science can be found at http://www.science.leidenuniv.nl/index.php/english/ and about Leiden University at http://workingat.leiden.edu/.
To apply for this vacancy, please send an email to Dr. Stefan Semrau (firstname.lastname@example.org) until June 18. Please include your curriculum vitae, a letter of motivation and the names of 3 potential references.