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Field
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clinical research on pharmacology, toxicology, and exposure science. Dr. Bernstein’s research team has access to outstanding facilities of Genomics, Genetics, Proteomics, Confocal and high-content imaging
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. genomics, transcriptomics, proteomics, imaging). Experience from interdisciplinary collaboration with biologists, clinicians, or industry partners. Experience in supervising or co‑supervising students
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populations. We will use diverse transcriptomic technologies, proteomics, and eCLIP to generate high-throughput information on miRNA, circRNA, and mRNA profiles in specialized cell populations
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
robust single cell-based foundation models on digital pathology images and will combine AI with our latest Deep Visual Proteomics workflow. For more information: group.szbk.u-szeged.hu/sysbiol/horvath
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expertise, including facilities for high-throughput screening and high content imaging, multimodality in vivo imaging, proteomics, spatial and single-cell transcriptomics. As part of King’s Health Partners
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, funded by Kempe fundation is full-time for two years with access may 2026 or by agreement. Departmental specific information The research group led by Jonas von Hofsten (https://www.umu.se/en/staff/jonas
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. The postdoc will work on a comprehensive translational research program combining advanced human iPSC-derived co-culture models, spatial transcriptomics and proteomics of patient skin biopsies, and mechanistic
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discovery and validation (e.g., microRNA, proteomics, diagnostics) Translational animal models of disease Excellent skills in scientific communication, project management, and leadership Ability to work
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high content imaging, multimodality in vivo imaging, proteomics, spatial and single-cell transcriptomics. As part of King’s Health Partners, we have an excellent environment for basic-clinical
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Postdoctoral Researcher in Bioinformatics and multiomics, your research focus will be on integrating and modelling patient transcriptome, metabolome and proteome data at single cell resolution with the aim