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on bioinformatics analysis of spatial gene expression data as well as other modalities (i.e. microbiome; metabolites, proteins) generated using the Spatial Transcriptomics (ST) method, Spatial metaTranscriptomics
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on methodological development in cryo-electron microscopy (cryo-EM), particularly in image reconstruction and 3D volumetric analysis of macromolecular structures. Rather than aiming to incrementally optimize existing
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, principal component analysis, analysis, analysis of kinship, trait analysis and metagenomic analysis (incl. analysis of pathogenic microorganisms). The bioinformatician is involved in maintaining, updating
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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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–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
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of the SciLifeLab Integrated structural biology platform https://www.scilifelab.se/units/structural-proteomics/ The unit provides access to cutting-edge equipment and expertise, for the analysis
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methods for detailed analysis of different RNA molecules in blood samples and contribute to a new research field with strong clinical potential. What you will work on The successful candidate will be
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for advanced molecular analysis. The facility’s mission is to make this powerful technology accessible by offering ISS services to the research community. The primary responsibility of this role is to conduct
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applicant’s responsibility to ensure that the application is complete in accordance with the instructions in the advertisement. Applications must include the following elements: Copies of diplomas and grades
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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