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Field
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of the Principal Investigator or his/her designate, including but not limited to the following: - Develop and improve framework of virome analyses, transcriptomic data analyses, metagenomic analyses or associated
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presentation, HLA expression, interferon-response signaling, HER2, or tumor-intrinsic immune evasion. Experience with epigenetics, chromatin biology, transcriptomics, DNA methylation, ATAC-seq, RNA-seq, or other
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genomics and transcriptomics, antibody development based on phage display, large-scale mass spectrometry-based proteomics, and associated bioinformatics. The department is also responsible for several
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project focuses on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High
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role of toxins derived from toxin-antitoxin systems in Mycobacterium tuberculosis and Mycobacterium abscessus by comparing the transcriptomes and proteomes in cells with or without toxin expression
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, methylation, and protein phosphorylation. Design, analyse and perform high-throughput -omics experiments, including RNA sequencing (RNA-seq), eCLIP, SLAM-seq, RIP-seq, and associated transcriptomic datasets
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analyse high-throughput -omics experiments, including RNA sequencing (RNA-seq), eCLIP, SLAM-seq, RIP-seq, and associated transcriptomic datasets invitro and in vivo. Investigate post-transcriptional
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, transcriptomics, proteomics), neuroimaging (PET, MRI), longitudinal clinical records, and digital pathology — reconciling differences in data type, format, spatial resolution, and dimensionality into unified
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cell immunology, mucosal immunology, and cancer immunology using animal models and single-cell multiomics/spatial transcriptomics approaches. This postdoctoral researcher will combine wet-lab molecular
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conditions by applying omics technologies (e.g., genomics, transcriptomics), validation of gene expression using quantitative reverse transcriptase polymerase chain reaction, and bioinformatic analyses