Postdoctoral Fellow - Computational Biology (100%)

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