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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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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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