This doctoral position focuses on integrating clinical, breath metabolomics, biomarker, lung function, and environmental exposure data to develop and apply multimodal ML methods. The candidate will model lung function trajectories from infancy to adolescence, perform external validation with different cohorts, and contribute to reproducible, well-documented code. Work involves close collaboration with interdisciplinary teams, including clinicians and exposure scientists.
(KI generierte Zusammenfassung)
... & Informatics for Child Health (AICH) group develops AI/ML methods, digital tools, and secure data pipelines to advance pediatric healthcare. We work at the intersection of clinical medicine, machine learning, and data-intensive research, collaborating closely with hospitals, clinical IT teams, and research partners at the University of Basel. The Project Preterm birth affects around 14 million infants each year and is a major risk factor for ...
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