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Data and Computing Technician (50%)
From June 1, 2027, or by agreement | initially fixed-term for 4 years, with the possibility of extension

The Department of Biomedical Engineering is part of the Faculty of Medicine at the University of Basel. It contributes to a better future in meeting health care needs through innovative biomedical research and engineering solutions, translating basic science into medical knowledge and healthcare innovations.

The Pediatric Disease Modeling Lab (https://dbe.unibas.ch/en/research/data-driven-modelling-analysis/pediatric-disease-modeling-lab/) is seeking a Data and Computing Technician to build and maintain the data and computing backbone of a growing research group. Our mission is to understand how early-life exposures to the microbiome shape lifelong health through their impact on the developing immune system. We develop mathematical models of microbiome–immune co-development to quantify how early-life perturbations to the microbiome shape antimicrobial resistance, infectious disease dynamics, and non-communicable diseases, with the aim of translating our insights into actionable strategies for pediatric care. Our work combines statistical and mechanistic mathematical modeling, causal inference, and machine learning, applied to longitudinal multi-omics data from pediatric cohorts spanning diverse socio-economic and geographical contexts.

Our lab will be supported by two major grants starting in 2027: RESILIENT (ERC Starting Grant), which synthesizes existing longitudinal multi-omics data from several pediatric cohorts across Africa, Asia, and Europe, and Restoring Homeostasis (SNSF Starting Grant), which generates new clinical multi-omics data from pediatric patients. These data arrive from different countries, sequencing platforms, and clinical metadata formats, and are subject to data-transfer agreements and data-protection requirements. Turning them into secure, well-documented, analysis-ready datasets, and providing the computational environment in which the team analyzes them, is the core of this position.
Your position
You will be responsible for the lab's research data and computational infrastructure: how data enter the lab, how they are stored, documented, and harmonized, and how the team's analyses run on the high-performance computing resources. You will work closely with the lab's Senior Scientist, who oversees the data-sharing agreements with our partners, and with the PI, postdocs, and PhD students who analyze the data. Your work ensures that every dataset entering the lab is secure, quality-controlled, and analysis-ready, and that the computational environment is reliable and reproducible.

In line with our and Uni Basel values (https://www.unibas.ch/en/Research/Values-Ethics/Diversity-and-Inclusion.html), we are committed to sustain and promote an inclusive culture, ensure equal opportunities and value diversity and respect in our working and learning environment.
Your main tasks will include:
Data management and governance: maintaining the lab's data management plans; implementing secure storage, access control, and pseudonymization in line with data-transfer agreements, ethics approvals, and Swiss and EU data-protection requirements; and organizing the secure receipt and transfer of data with partner cohorts
Research computing: managing the lab's compute and storage resources on the University of Basel's high-performance computing infrastructure (sciCORE), maintaining software environments and shared tooling, and providing first-line IT support to the team
Building and maintaining reproducible data-processing pipelines (e.g., Snakemake or Nextflow, containers, version control)
Data harmonization: standardizing clinical metadata across cohorts with different data-collection protocols, and building a common data dictionary
Sequencing data processing: quality control and taxonomic classification of 16S and shotgun metagenomic data, and processing of other omics layers where needed
Creating and versioning analysis-ready datasets for the modeling team, with clear documentation and provenance tracking
Documenting data and workflows, and supporting team members in data access and best practices
Your profile
Essential:
Degree (BSc or MSc) in bioinformatics, computer science, data science, or a related field, or equivalent professional experience
Solid experience with Linux, Git, high-performance computing environments, and scripting in Python and/or R
Experience processing sequencing data, in particular microbiome (16S or shotgun metagenomic) data
Experience with data-management practices: data documentation, versioning, quality control, and structured data formats or databases
Excellent written and spoken English, and the ability to communicate effectively with scientists
Desirable:
Experience with workflow managers (Snakemake, Nextflow), containers (Docker, Singularity/Apptainer)
Familiarity with data-protection requirements for health data (e.g., GDPR, Swiss Human Research Act) and with pseudonymization or secure data-transfer procedures
Experience with clinical or cohort study data and metadata standards
Knowledge of German is an asset but not required
We offer you

A key technical role in expanding a research group funded by two major starting grants, with a four-year contract and the possibility of extension
Work with unique longitudinal datasets from international pediatric cohorts
A stimulating, interdisciplinary environment at the intersection of computational science and pediatric health, embedded in Basel's life-sciences ecosystem
Close collaboration with the University of Basel's scientific computing center (sciCORE) and with clinical and academic partners
A dynamic and supportive team culture that values diversity and inclusion
Salary and social benefits according to the regulations of the University of Basel

Key References

B. Tepekule, A.I. Lim, and C.J.E. Metcalf, "The ontogeny of immune tolerance: a model of early-life secretory IgA - gut microbiome interactions", PLoS Biology, 2025.
Link: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003263

B. Tepekule, J. Bergadà-Pijuan, T. Scheier, H. F. Günthard, M. Hilthy, R. D. Kouyos, S. Brugger, "Computational and in vitro evaluation of probiotic treatments for nasal Staphylococcus aureus decolonization", Proceedings of the National Academy of Sciences (PNAS), 2025.
Link: https://www.pnas.org/doi/10.1073/pnas.2412742122

B. Tepekule, P. Abel Zur Wiesch, R. Kouyos, S. Bonhoeffer, "Quantifying the impact of treatment history on plasmid-mediated resistance evolution in human gut microbiota", Proceedings of the National Academy of Sciences (PNAS), 2019.
Link: https://www.pnas.org/content/116/46/23106