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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 6 days ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Candidate (f/m/x) - Organelle Biology and Proteomics in
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cells. Proteomic approaches have identified several surface proteins that are overexpressed in glioblastoma stem cells compared with non-tumour cells, and whose role in glioblastoma biology remains to be
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, or representation learning. Experience analysing large-scale single-cell omics data. Experience with integrative multi-omics data, such as genomics, proteomics, or metabolomics. Experience with relevant machine
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create mouse chronic kidney disease. Works on high throughput data analysis that includes data from single cell sequence, CHIP-Seq, and proteomics. Conducts molecular assays such as real time RT-PCR
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Professor in Biomarker Discovery and Clinical Proteomics in the Department of Medicine, School of Clinical Medicine (Ref.:537311) We now invite applications for the captioned post. Duties and Responsibilities
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electron microscopy (cryo-EM), light microscopy, sequencing, and proteomics. For more information, please visit https://www.helsinki.fi/hilife/bi Additional information For further inquiries regarding
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, or representation learning. Experience analysing large-scale single-cell omics data. Experience with integrative multi-omics data, such as genomics, proteomics, or metabolomics. Experience with relevant machine
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Max Planck Institute for Heart and Lung Research, Bad Nauheim | Bad Nauheim, Hessen | Germany | 12 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
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Location: Central Cambridge We are seeking applications for a PhD position in AI in proteomics as part of the Horizon Europe MSCA Doctoral Network, ProtAIomics. This brings together laboratories
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variation as an anchor for causal inference across molecular layers (genomics, transcriptomics, proteomics, and metabolomics), enabling more principled identification of disease-relevant proteins and pathways