Daan Geijs studied Biomedical Engineering at the University of Twente and specialized in Image and Diagnostics. Subsequently, he finished his master thesis segmenting tumor by applying deep learning on fluorescent multiplex breast cancer images in 2019. In the same period, he finished the master study Science Education and Communication in Physics and worked as a secondary school Physics teacher. In March 2020 he started as PhD candidate in the Computational Pathology Group and Diagnostic Image Analysis Group where he works under the supervision of Geert Litjens implementing deep learning in the daily routine of pathologists assessing skin cancer.

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