Ruprecht-Karls-Universität Heidelberg

Anders Group: Open positions

Analysis of single-cell sequencing data

Single-cell sequencing offers exciting new means to study the interplay between cell types making up tissues and organs, in health and disease, but making full use of thise new type of data requires sophisticated bioinformatics. The Anders group at the Center for Molecular Biology of Heidelberg University is developing bioinformatical tools and statistical methods to process and interpret big data in biomedical studies, with a focus on single-cell assays. We are seeking

two computational scientists

to join our team. We welcome applications not only from bioinformaticians but also from physicists, mathematicians, computer scientists, statisticians, data scientists, engineers or from any other computational discipline. Prior experience in molecular biology is a plus, but not required.

Currently, we have openings for one PhD student and one post-doc.

For the post-doc position, we hope for prior experience in coding, scientific software development or data analysis, and some deeper understanding of multidimensional statistics, applied linear algebra or data science; for the PhD student position we expect a basic understanding of these topics, and potential to learn more.

We work in close collaboration with outstanding experimental biologists and physicians-scientists, and hence offer unique opportunities to develop and apply sophisticated biostatistical ideas for practical applications in cutting-edge biomedical research.

Specifically, the two vacancies are associated with the following two projects:

  • Characterization of lymphoma with single-cell analysis: In collaboration with the research group of Dr Sascha Dietrich, oncologist at Heidelberg University Hospital, we are researching how lymphoma and leukaemia samples differ between patients with respect to cellular composition and transcriptional programmes of tumour and immune cells, in order to understand what determines success and failure of drug treatments and what causes relapses. We have started to perform single-cell sequencing and other omics assays on a large number of lymphoma samples and whish to expand our team on the computational side, to develop new statistical methods to compare single-cell RNA-Seq over large numbers of samples. This project has a theoretical side – how to deal with the hierarchical structure of the data (several disease groups, each group has several samples, each sample comprising thousands of cells assayed for thousands of genes) when performing data reduction and inference –, and an applied side – to analyse our specific data and to draw clinically relevant conclusions, in discussions with the oncologists in the team.

  • Single-cell transcriptomics in zonated tissue: In many tissues, the transcriptional programme of cells varies smoothly with microanatomical structure ("zonation"), and we need computational methods to characterize such gradients and compare them between samples, to better understand how the cells in a tissue work together to achieve its physiological function. This project is part of the newly founded Collorative Research Centre CRC1366 on interactions between the cells of the blood vessels and those of the surrounding organs. Our group will not only develop methods to deal with the zonation and other properties of single-cell assays of blood vessels, but also collaborate with the other groups in the CRC, which will use single-cell RNA-Seq to study blood vessels in various biological tissues, and advise them on the analysis and interpretation of their experiments.

For both projects, we need scientists with ability to think mathematically, but also with enthusiasm for biology, and skills to communicate with experimentalists and translate between theory and application.

Please send your application to Dr. Simon Anders, Please include a CV, a cover letter with details on your skills and prior experience. If possible, please also include a "work sample" that show-cases you programming skills, e.g., some code you have written for a project or a course home work.

updated 2019-06