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and experimental models. Our research focuses on combining large-scale molecular data - including metabolomics, lipidomics, genomics, proteomics, glycomics, and microbiome data - with advanced
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, single-cell transcriptomics, proteomics, metabolomics, and network reconstruction. Former trainees of the Chi lab have been principal investigators in multiple academic institutions. Please also see the
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, manuscripts, and presentations. Analyze high-throughput datasets, including RNA-seq and proteomics data. Collaborate with internal and external research teams. FLSA Exempt Grade Salary Details Minimum Salary
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Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences (formerly Institute of Genetics and Animal Biotechnology PAS) | Poland | about 2 months ago
, transcriptomic, proteomic, and epigenomic phenomena in blood leukocytes/serum and mammary secretory tissue of SRLV-infected goats with an acute versus mild course of CAE. This study serves as a continuation and
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biological systems, inflammatory diseases, or diverse clinical patient sample data. Familiarity with processing and analyzing multi-omics datasets (e.g., metagenomics, metabolomics or proteomics) integrated
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proteomics, including protein identification, quantitation, and thermal proteome profiling, and in mass spectrometry-based targeted and untargeted metabolomics. In addition, the candidate should have
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bioinformatics: i.e., analyzing -omics data, e.g., transcriptomics, proteomics, and/or metabolomics (fungal and/or insect), (3) fungal cell biology including microscopy, e.g., fluorescent and confocal, (4) fungal
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field. Experience with mammalian cell engineering, CRISPR screens, and proteomics. Experience with C. elegans genetics. Experience in antibody engineering, molecular biology, cell biology, biochemical
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of molecular networks in cancer to advance precision medicine. By integrating high-throughput data (e.g. transcriptomics, proteomics, metabolomics) with prior knowledge of molecular interactions, we construct
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the time the employment decision is made. Strong understanding of biological datasets and data modalities relevant to cell biology, such as imaging, transcriptomics, proteomics, or spatial omics Rich