Work on an own scientific qualification project (doctorate)., Develop, coordinate, manage and publish research projects within the field of “Upscaling geological heterogeneity at the pore scale using deep learning”., Develop deep learning workflows for super-resolution imaging, heterogeneity upscaling, and property prediction., Reconstruct digital twins of rock samples at multiple scales through image processing, scan registration, noise reduction, and AI-based segmentation., Acquire, process, and analyse multi-scale X-ray CT datasets to evaluate pore- and core-scale heterogeneity., Validate deep learning predictions against laboratory-scale measurements (porosity, permeability, NMR, MICP, Darcy-scale flow tests)., Perform numerical simulations at the pore and core scale to estimate flow and transport properties., Support and contribute to multiscale sample characterization, including XRD, SEM/FIB-SEM, µXRF, BET, MICP, NMR, and geochemical analyses., Present results at national and international conferences and contribute to high-impact journal publications., Contribute to project organisation, documentation, and reporting in coordination with national partners., Support teaching activities of the institute (e.g., exercises, supervision of student assistants, BSc/MSc theses).