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, single-cell mRNA transcriptomics, and quantitative/functional antibody assays in human and animal models. Responsibilities The postdoctoral associate will – based on their research interest: Design and
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microbial research using genomic, transcriptomic, metabolomic, fluxomic, and other multi-omics approaches. Perform laboratory-based molecular microbiology experiments, including microbial cultivation and
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Immune Metabolism Modeling Scientist, you will: Lead the development, validation, and application of genome-scale metabolic models using in-house computational tools. Integrate transcriptomics, proteomics
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of infection or inflammation, innate immunity, and/or transcriptomic or proteomic approaches. The research environment offers access to a broad spectrum of state-of-the-art immunological techniques, including
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morphology. Design, coordinate and interpret bulk RNA-sequencing experiments with the project bioinformatician. 'Analyse, interpret and integrate experimental data from cellular, imaging and transcriptomic
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bioinformatics applications in cancer research Utilize advanced computational and bioinformatics approaches to analyze genomic, transcriptomic, proteomic, and other large-scale biological datasets. Publish
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, transcriptomic, or phenotypic datasets. Collaborate with the Research Software Engineering (RSE) team to support the curation, independent verification, and presentation of findings through web-based interactive
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of reporter systems to monitor RNA-mediated gene regulation Functional characterization of candidate riboswitches in cultured cells Transcriptomic and gene expression analyses Investigation of lithium- and
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | about 2 months ago
. The successful candidate will participate in scientific research projects involving biological samples and advanced analytical technologies, including spatial transcriptomics, digital pathology, molecular biology
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on neurodevelopmental disorders. The successful candidate will apply computational approaches to analyze high-throughput biological data, including genomics, transcriptomics, and proteomics datasets. You will collaborate