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stem cells and primary patient cells), and techniques (CRISPR gene editing, ATAC-, ChIP-, RNA-seq and label-free quantitative mass spec) will be used with the goal to gain a better insight in disease
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in CT images. To achieve this, the project will leverage multi-modal AI technologies, integrating a diverse array of data sources, including radiological text data, primary tumor locations, and
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are trained in radiation physics, radiation biology, radiation safety, or dosimetry. Further you recognize yourself in the profile below: Masters degree in (bio)physics, health physics, technical
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complaints and improvement of quality of life. Together with the German PhD-student, you will perform the proposed studies. You will be the main spokesperson for all partners involved in this project. You will
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time in the world. These technical aspects must be combined and tested in phantoms, animal studies, and in case of positive results, also in patients. The combined techniques will be the main part of