Exploring Individual Immune Responses through Machine Learning – From Infection to Intervention
David Hillus, Josephina Hillus, Charité - Universitätsmedizin Berlin, Klinik für Infektiologie und Intensivmedizin
Inhalte/ Contents
Why do some individuals develop severe infections or fail to mount sufficient immunity after vaccination? Investigating this question with machine learning and diverse open-access datasets offers opportunities to uncover drivers of immune variability and inform precision medicine. In this research group, students will integrate immunological, clinical, and genetic data to identify factors shaping individual responses. They will cluster immune profiles, develop predictive models to detect risk factors, and test model generalizability across populations. The project bridges biology and computation, providing hands-on training in data analysis, model interpretation, and bias assessment, and equipping students with essential AI skills for the digital research landscape.
Kontakt/ Contact
david.hillus@charite.de