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The Laboratory of Exercise and Health, headed by Prof. Dr. Katrien De Bock at the Department of Health Sciences and Technology (D-HEST), ETH Zurich, is offering a fixed-term position for a bioinformatician (postdoctoral level) to lead the single-cell and spatial transcriptomics analyses within the laboratory of Exercise and Health

The Laboratory of Exercise and Health investigates how the muscle microvascular niche – and in particular heterogeneous and specialized endothelial cell (EC) subpopulations – interacts with other niche cells (e.g. macrophages, pericytes, fibro-adipogenic progenitors) to maintain skeletal muscle homeostasis, and how disruption of this crosstalk contributes to muscle dysfunction. The research of the Laboratory of Exercise and Health combines human patient samples, mouse genetic models, single-cell and spatial transcriptomics, and in vivo cell-cell interaction tracing with CRISPR perturbation to mechanistically dissect EC-niche communication

The lab offers a highly collaborative, international research environment at the interface of vascular biology, muscle physiology, and metabolism. For more information on the lab, visit

Job description

You will lead all single-cell and spatial transcriptomics work, working closely with an international team of PhD students and postdocs and in direct collaboration with Prof. De Bock. Specific responsibilities include:

Design, execute, and interpret scRNAseq analyses of human (patient-derived) and mouse skeletal muscle samples, identifying and annotating cell (sub)populations. Discuss and design follow-up wet lab experiments with colleagues

Integrate scRNAseq datasets with other omics information, including spatial transcriptomics, ATAC sequencing, metabolomics and/or multiplex imaging data

Perform cross-species (human–mouse) data integration to identify conserved and divergent cellular and molecular signatures of PAD

Apply and further develop computational tools for cell-cell communication analysis (ligand-receptor interactions and signaling pathways) and constraint based metabolic modeling tools (e.g. COMPASS, scFEA) to link transcriptional states to cell metabolism

Analyze single-cell datasets generated from in vivo cell-cell interaction tracing models

Perform pseudobulk and differential expression analyses (e.g. edgeR) of scRNAseq/5’ECCITE-seq data from CRISPR perturbation screens

Apply in silico perturbation approaches to nominate candidate regulators of cellular crosstalk for downstream functional validation

Build, document, and maintain reproducible bioinformatics pipelines, and support other lab members with transcriptomics and genomics data

Designing Shiny apps for data visualization for internal and possibly external use in publications

Contribute to manuscript preparation, data visualization, and project reporting, and stay current with emerging single-cell and spatial genomics methods

Profile

PhD degree in bioinformatics, computational biology, computational genomics, or a related quantitative field

Demonstrated hands-on experience analyzing single-cell RNA sequencing data (e.g. Seurat, Scanpy) from raw data processing through downstream analysis; experience with spatial transcriptomics is a strong plus

Excellent scripting and data analysis skills in R and/or Python, with in-depth knowledge of relevant Bioconductor/scverse packages

Strong experience with collaborative development environments (e.g. GitHub/GitLab), version control, and maintaining well-documented, reusable repositories

Working experience with high-performance computing environments

A strong interest in skeletal muscle physiology and/or vascular biology; prior research exposure to these fields is a plus but not required

Good understanding of biological research questions and enthusiasm for close collaboration with wet-lab researchers

Strong communication skills, a team-oriented and service-minded approach, and the ability to work independently and take ownership of a research area

Advanced proficiency in English

A unique opportunity to lead the single-cell genomics workflow in a dynamic, collaborative, and internationally oriented lab. You will have access to state-of-the-art infrastructure at ETH Zurich, dedicated computational resources, and close interactions with other bio-informaticians within the institute as well as the Functional Genomics Center Zurich (). We offer a competitive salary in line with ETH Zurich regulations

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity, and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected

Working, teaching and research at ETH Zurich

We value diversity and sustainability

climate-neutral future

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow