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and contributing to research projects in genomics and proteomics, performing relevant statistical and bioinformatics analyses, and integrating the research group’s genomics and proteomics data with
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-disciplinary team and will be trained in biochemistry, molecular biology, proteomics, genomics (ChIP-seq, RNA-seq, ATAC-seq etc) in cell and primary disease models. This PhD role will also be embedded in a
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, demonstrable experience in mass spectrometry-based proteomic analysis or in RNA sequencing, as well as a background in immunology and biochemistry; - Experience in quantitative proteomics data analysis and de
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candidate will contribute to the establishment and validation of multiplex spatial biology and proteomic panels for cancer research, supporting innovative translational research projects and collaborations
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position within a Research Infrastructure? No Offer Description Activities and context The successful candidate will join a multidisciplinary project spanning immunology, oncology, proteomics, genomics
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fragmentation approaches utilised in the field of proteomics; the ability to carry out analytical procedures that are applied for proteome characterisation to a high degree of precision; able to analyse
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, methylome and proteomic data. This is more than a data analysis role. You’ll have the opportunity to influence experimental design, identify interesting patterns and signatures within large datasets and help
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of Medical Sciences We are seeking a highly motivated and enthusiastic Postdoctoral Research Associate with an interest in human plasma proteomics to join a pioneering project exploring the links between
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Are you passionate about mass spectrometry and are you experienced in running high resolution mass spectrometry proteomics? Department of Food Science at Aarhus University is looking
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Max Planck Institute for Heart and Lung Research, Bad Nauheim | Bad Nauheim, Hessen | Germany | 13 days ago
diseases. Our group investigates how cells sense stress, mount adaptive responses, and restore homeostasis to maintain cellular resilience. We combine human cellular models with transcriptomic and proteomic