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Field
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diverse sources of biological information, including the biophysical principles governing protein–DNA interactions, the genetic and epigenetic features of DNA sequences, and the three-dimensional (3D
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–DNA interactions, the genetic and epigenetic features of DNA sequences, and the three-dimensional (3D) organization of the genome and its regulatory landscape. A particular focus will be on integrating
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–DNA interactions, the genetic and epigenetic features of DNA sequences, and the three-dimensional (3D) organization of the genome and its regulatory landscape. A particular focus will be on integrating
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diverse sources of biological information, including the biophysical principles governing protein–DNA interactions, the genetic and epigenetic features of DNA sequences, and the three-dimensional (3D
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learning, dynamical systems, sequence generative models and world modelling. Emphasis will be on methods that design and implement new architectures for latent dynamic modelling to enable identification
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for simulation experiments and analyzing genomic sequencing data; (2), designing, implementing, and overseeing research projects focused on methods development for understanding genetic variation within and
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present results at team meetings to share results, plan projects and experiments. · Work with other computational biologists experienced with various sequencing technologies, including those
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: • Design and execute single-cell genomic experiments (e.g., single-cell RNA sequencing and related single-cell/multi-omic assays) on patient-derived and model samples. • Contribute to high-throughput
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blotting and immunoprecipitation Drug response assay, determination of IC50 etc. Analysis of big datasets (e.g. RNA-sequencing) Working with animals (not essential, but preferential). Ability to assess
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-nucleus RNA sequencing (snRNA-seq) datasets to characterize post-metamorphic cell types and investigate their developmental dynamics. The project includes the generation of cell type-specific bulk ATAC-seq