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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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experimental data are now available or it may use population-scale genetic, clinical, or public health data from pathogen surveillance efforts and biobanks. The future of life science is data driven. Will you be
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. Experience in DNA repair assays, cytogenetics, plant functional genetics, transgenics/CRISPR, or advanced microscopy is a strong additional merit. Location: Uppsala. Form of employment: Employment as a
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evaluate them on experimental cryo-EM datasets. Cryo-EM is a rapidly growing field that has transformed structural biology over the past decade. The methods are proven and impactful, yet far from mature
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credits, or Mandatory requirement for English equivalent to English B/6 Experience in formulating lipid nanoparticles with mRNA via microfluidics Experience in sample preparation and data analysis from
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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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experience with work with human cancer cell lines, stem cells, and/or immunohistochemistry is a plus Programming skills with Python or R is a plus Excellent communication skills A solid experimental or