PhD position in Computational Biology (100%)
University of Basel is among the world’s best universities and holds a top‑ten spot among German‑speaking universities.
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) offers a PhD research opportunity in systems biology and mathematical modelling. 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 shape infectious disease dynamics, vaccine responses, and non‑communicable diseases, aiming to translate insights into actionable strategies for pediatric care. Our work combines mechanistic mathematical modelling, causal inference, and machine learning approaches, and can be applied to longitudinal multi‑omics data from pediatric cohorts spanning diverse socio‑economic and geographical contexts.
We are seeking a highly motivated PhD student to join our interdisciplinary research team. You will have the opportunity to apply cutting‑edge quantitative methods and modelling approaches to diverse datasets with longitudinal multi‑omics data from both local and international collaborations. You will be part of a collaborative research environment with close interactions with the Basel Research Centre for Child Health (BRCCH), the University Children’s Hospital Basel (UKBB), and the Swiss Tropical and Public Health Institute (Swiss TPH).
A strong interest in applying mathematical modelling to biological questions and excellent teamwork and communication skills in English are required. The PhD candidate will be expected to take an active role in shaping the project within an environment that encourages academic freedom and scientific independence.
In line with our and Uni Basel values (https://www.unibas.ch/en/Research/Values-Ethics/Diversity-and-Inclusion.html), we are committed to sustaining and promoting an inclusive culture, ensuring equal opportunities, and valuing diversity and respect in our working and learning environment.
Main tasks
* Analyzing and integrating longitudinal multi‑omics data from pediatric cohorts
* Developing and parameterizing mechanistic mathematical models
* Applying statistical modelling, causal inference, and machine learning approaches
* Collaborating with experimental and clinical research partners
* Supporting and preparing scientific reports and journal articles
Essential qualifications
* Master’s degree in Computational Biology, Bioinformatics, Applied Mathematics, Physics, Statistics, Computer Science, Engineering, or a related quantitative field
* Strong interest in applying quantitative methods to biomedical questions
* Experience with programming (e.g., Python, R, or MATLAB)
* Excellent written and spoken English communication skills
* Motivation to work in an international research environment
Desirable qualifications
* Experience with statistical or mechanistic modelling or machine learning
* Familiarity with biological data analysis (e.g., microbiome, transcriptomics, or immunological data)
* Background in dynamical systems, Bayesian inference, or causal inference
* Interest in global health, immunology, or developmental biology
Benefits and environment
* Access to unique longitudinal datasets from international pediatric cohorts
* Close collaboration with clinical partners and an international network of researchers
* Strong mentorship with opportunities for career development and scientific independence
* Participation in the PhD program in Biomedical Engineering at the University of Basel
* A dynamic and supportive team culture that values diversity and inclusion
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.
* 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.
* 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://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003263
Link: https://www.pnas.org/doi/10.1073/pnas.2412742122
Link: https://www.pnas.org/content/116/46/23106
Application / Contact
The position is available from August 1, 2026, or later by mutual agreement. Review of applications will begin immediately and continue until the positions are filled. Please submit your application via the University of Basel Recruiting‑Portal, by submitting the following documents: (A) a cover letter describing your research interests and motivation; (B) a complete curriculum vitae; (C) contact details of at least two references willing to provide recommendation letters upon request.
For informal inquiries about the position, please contact Prof. Dr. Burcu Tepekule (burcu.tepekule@unibas.ch).
The University of Basel is an equal opportunity and family‑friendly employer committed to excellence through diversity.
Job details
Title: PhD position in Computational Biology (100%)
#J-18808-Ljbffr