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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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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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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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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study