Bioinformatician – Single-Cell Omics in Vascular & Skeletal Muscle Biology

The Laboratory of Exercise and Health at ETH Zurich seeks a Bioinformatician, Single‑Cell Omics to steer its single‑cell and spatial transcriptomics pipeline. The group investigates how endothelial cell subpopulations within the muscle microvascular niche interact with surrounding cells to preserve skeletal‑muscle homeostasis and how their disruption leads to dysfunction. The position sits in a highly collaborative, international environment that bridges vascular biology, muscle physiology and metabolism. In this role you will design, run and interpret single‑cell RNA‑sequencing projects on both human patient material and mouse muscle tissue, annotating distinct cell (sub)populations. You will work with colleagues to plan complementary wet‑lab experiments, merge scRNA‑seq data with spatial transcriptomics, ATAC‑seq, metabolomics or multiplex imaging, and perform cross‑species integration to uncover conserved signatures. Computational tasks include building and extending tools for ligand‑receptor communication, applying constraint‑based metabolic models such as COMPASS or scFEA, and conducting pseudobulk and differential expression analyses for CRISPR perturbation screens. You will also create reproducible pipelines, support lab members with genomics data, develop Shiny applications for visualisation, and contribute to manuscript figures and project reports while staying abreast of emerging single‑cell technologies. The successful candidate must hold a PhD in bioinformatics, computational biology, computational genomics or a comparable quantitative discipline. Proven hands‑on expertise in processing and analysing single‑cell RNA‑seq data from raw reads through downstream interpretation is essential, as is strong programming ability in R and/or Python together with familiarity with Bioconductor/scverse packages. Robust experience with collaborative development platforms such as GitHub or GitLab, version‑control practices and well‑documented, reusable code repositories is required. The role also demands practical experience with high‑performance computing infrastructures and fluency in English at an advanced level. Additional assets include prior work with spatial transcriptomics and a genuine interest in skeletal‑muscle physiology or vascular biology, which would facilitate deeper engagement with the laboratory's scientific questions. The position offers access to ETH Zurich's cutting‑edge computational resources, close interaction with other bioinformaticians, and a supportive, inclusive culture that values diversity, equality and sustainability. A competitive salary follows ETH Zurich regulations, and the role provides a unique chance to lead a core genomics workflow within a vibrant, interdisciplinary team. What the role asks for: - PhD in bioinformatics or related quantitative field - Hands‑on experience with single‑cell RNA‑seq analysis - Proficient scripting in R and/or Python (Bioconductor/scverse) - Strong use of GitHub/GitLab and version control - Experience with high‑performance computing environments - Advanced proficiency in English - Experience with spatial transcriptomics (nice‑to‑have) - Interest in skeletal muscle physiology or vascular biology (nice‑to‑have)