Postdoctoral Fellow - Computational Biology (100%) 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 post-doctoral research opportunity in the context of 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, with the aim of translating our insights into actionable strategies for pediatric care. Our work combines mechanistic mathematical modeling, causal inference, and machine learning approaches, with the opportunity to be applied to longitudinal multi-omics data from pediatric cohorts spanning diverse socio-economic and geographical contexts. Your position We are seeking a highly motivated postdoctoral researcher to join our interdisciplinary team. You will develop and apply advanced statistical and causal inference methods to characterize developmental trajectories from longitudinal multi-omics data, with the goal of understanding how early-life perturbations shape long-term health outcomes across diverse pediatric populations. You will have the opportunity to work with rich datasets from international pediatric cohorts spanning diverse geographic and socioeconomic contexts, including 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. 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. Depending on your interests and background, your work may involve: Developing methods to characterize developmental patterns from multi-omics data Developing and parameterizing mechanistic mathematical models describing microbiome-immune dynamics Applying Bayesian inference and model fitting approaches Applying statistical modeling, causal inference, and machine learning approaches to identify determinants of developmental robustness Applying causal inference approaches to identify critical windows in development Optimizing intervention strategies through computational experimentation Collaborating with experimental and clinical research partners Contributing to scientific publications and grant applications Your profile Essential: PhD in biostatistics, epidemiology, computational biology, or a related quantitative field Strong background in statistical modeling and causal inference methods Experience with longitudinal data analysis Interest in developmental biology, immunology, or pediatric health Proficiency in scientific programming (e.g., R, Python, or Julia) Excellent communication and writing skills in English Desirable: Experience with multi-omics data integration or microbiome data analysis Familiarity with Markov models or trajectory analysis methods We offer you A stimulating, interdisciplinary research environment at the intersection of statistics and pediatric health Access to rich longitudinal datasets from international collaborations Close collaboration with clinical and experimental research groups Competitive salary according to Swiss National Science Foundation guidelines Support for career development and conference participation 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/doi/10.1073/pnas.1912188116 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. Apply www.unibas.ch Wenn Sie sich auf diese Stelle bewerben, erwähnen Sie bitte dass Sie sie auf Universitoxy gesehen haben.

Postdoctoral Fellow - Computational Biology (100%)

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 post-doctoral research opportunity in the context of 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, with the aim of translating our insights into actionable strategies for pediatric care. Our work combines mechanistic mathematical modeling, causal inference, and machine learning approaches, with the opportunity to be applied to longitudinal multi-omics data from pediatric cohorts spanning diverse socio-economic and geographical contexts.

Your position

We are seeking a highly motivated postdoctoral researcher to join our interdisciplinary team. You will develop and apply advanced statistical and causal inference methods to characterize developmental trajectories from longitudinal multi-omics data, with the goal of understanding how early-life perturbations shape long-term health outcomes across diverse pediatric populations.
You will have the opportunity to work with rich datasets from international pediatric cohorts spanning diverse geographic and socioeconomic contexts, including 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. 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.

Depending on your interests and background, your work may involve:

Developing methods to characterize developmental patterns from multi-omics data
Developing and parameterizing mechanistic mathematical models describing microbiome-immune dynamics
Applying Bayesian inference and model fitting approaches
Applying statistical modeling, causal inference, and machine learning approaches to identify determinants of developmental robustness
Applying causal inference approaches to identify critical windows in development
Optimizing intervention strategies through computational experimentation
Collaborating with experimental and clinical research partners
Contributing to scientific publications and grant applications

Your profile

Essential:

PhD in biostatistics, epidemiology, computational biology, or a related quantitative field
Strong background in statistical modeling and causal inference methods
Experience with longitudinal data analysis
Interest in developmental biology, immunology, or pediatric health
Proficiency in scientific programming (e.g., R, Python, or Julia)
Excellent communication and writing skills in English

Desirable:

Experience with multi-omics data integration or microbiome data analysis
Familiarity with Markov models or trajectory analysis methods

We offer you

A stimulating, interdisciplinary research environment at the intersection of statistics and pediatric health
Access to rich longitudinal datasets from international collaborations
Close collaboration with clinical and experimental research groups
Competitive salary according to Swiss National Science Foundation guidelines
Support for career development and conference participation

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/doi/10.1073/pnas.1912188116

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.

Apply

www.unibas.ch

Wenn Sie sich auf diese Stelle bewerben, erwähnen Sie bitte dass Sie sie auf Universitoxy gesehen haben.

Bewerbung

Mehr