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assays, complemented by mass-spectrometry-driven chemical profiling and machine-learning-supported multivariate analysis. Where relevant, CRISPR-Cas-based genetic perturbations in mammalian cell models
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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highly interdisciplinary setting combining microbial mutagenesis assays, mammalian cancer models, next-generation sequencing, bioinformatics, and machine learning. Experimental data will be integrated with
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