Your position

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 modeling 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.

Depending on your interests and background, your main tasks will include:

Analyzing and integrating longitudinal multi-omics data from pediatric cohorts
Developing and parameterizing mechanistic mathematical models
Applying statistical modeling, causal inference, and machine learning approaches
Collaborating with experimental and clinical research partners
Support and preparation of scientific reports and journal articles

Your profile

Essential:

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:

Experience with statistical / 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

We offer you

A stimulating, interdisciplinary research environment at the intersection of computational science and pediatric health

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

Your position

Depending on your interests and background, your main tasks will include:

Analyzing and integrating longitudinal multi-omics data from pediatric cohorts
Developing and parameterizing mechanistic mathematical models
Applying statistical modeling, causal inference, and machine learning approaches
Collaborating with experimental and clinical research partners
Support and preparation of scientific reports and journal articles

Your profile

Essential:

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:

Experience with statistical / 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

We offer you

A stimulating, interdisciplinary research environment at the intersection of computational science and pediatric health

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

Your position

Depending on your interests and background, your main tasks will include:

Analyzing and integrating longitudinal multi-omics data from pediatric cohorts
Developing and parameterizing mechanistic mathematical models
Applying statistical modeling, causal inference, and machine learning approaches
Collaborating with experimental and clinical research partners
Support and preparation of scientific reports and journal articles

Your profile

Essential:

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:

Experience with statistical / 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

We offer you

A stimulating, interdisciplinary research environment at the intersection of computational science and pediatric health

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

PhD position in Computational Biology (100%)

University of Basel

Peterspl. 1, 4001 Basel, Switzerland