PhD Student in Radio-Multiomics for Chronic Lung Diseases

Tasks

• analyze and integrate multiomics datasets (e.g. sc/snRNA-seq, spatial transcriptomics, highly multiplexed immunofluoresence)
• combine molecular profiles with radiological / radiomic imaging features
• develop multimodal integration and radio-multiomics approaches
• apply machine learning / deep learning methods for mechanistic discovery, disease stratification, and predictive modeling
• collaborate closely with clinicians, biologists, and computational scientists.

Requirements

• a highly interdisciplinary PhD project at the interface of bioinformatics, (bio-) medical imaging, and precision medicine
• access to unique multimodal datasets and well-characterized clinical cohorts
• a collaborative and internationally connected research environment
• strong opportunities for scientific development, publication, and career growth.

Benefits

• International reputation