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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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models in more detail using a wide range of methodologies and tools (e.g. molecular cloning and genome editing, immunoblotting, flow cytometry, high-resolution imaging and proteomics/terminomics). With its
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hotspots, and they are exceptionally beautiful. We will use a combination of molecular tools, quantitative genetics, and population genetic modelling to study genetic diversity in DNA sequence and phenotype
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. “Bioengineering Personalized Disease Avatars for Precision Hemato-Oncology” (working group of Prof. Simon Haas) 3. “Molecular and Cellular Determinants of Precancer Progression for Risk Stratification