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computing education. SciLifeLab BIIF is administratively placed here, and offers education and research support within digital image processing and analysis for life science applications. Science for Life
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incorporate it into mathematical models of trait evolution across phylogenies. The work combines dimensionality reduction and geometric data analysis with the development of statistically rigorous comparative
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methods for analysis of cellular and molecular biology data. The host institution, The Department of Gene Technology , is the most prominent research environment at KTH, according to bibliometrics
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analysis of such data will thus be a core activity in the doctoral program. Furthermore, performing flow cytometry analyses and cell sorting will be central and also immunological assays will be used
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biomarkers in body fluids. We are seeking a data scientist dedicated to clinical proteomics and biomarkers discovery and validation studies. This role will focus on building robust data management and analysis
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processes. Projects can include assembling, sharing, integrating, and advanced analysis of large amounts of data from diverse sources, including experiments, observations, and simulations, to gain a deeper
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research service in the comprehensive analysis of chemical contaminants and small molecules in human and environmental samples by target and nontarget mass spectrometry, also called chemical exposomics. Main
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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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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning
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–based studies for protein quantification and comparative analysis, to specialized applications in glycomics and glycoproteomics. We use Orbitrap and timsTOF mass spectrometers interfaced with LC systems