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dynamic interactions and complexity of the proteome and manipulate protein targets and their function. Ultimately our work helps to identify novel biological mechanisms underlying diseases, such as cancer
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-based bioinformatics tools. Transfers abstract workflows into production level software. Analyzes and interprets data of high throughput genomics, proteomics and genetic data. Customizes existing
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ovarian cancer. The laboratory has about 15 members that use cutting-edge methods, including spatial proteomics, spatial metabolomics, spatial transcriptomics, 3D organotypic cultures of human tissue, in
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on mechanistic insights into tumor biology with an emphasis on signaling, metabolism, and immunology and a goal to translate scientific discovery into the clinic. Appointees are expected to direct a proteomics
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regeneration Machine-learning foundations for multimodal integration of data across genomics, metagenomics, proteomics, metabolomics, imaging, clinical records, and other data modes Developing biologically
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and immunity · Spatial, systems, and computational cancer or immunology · Single-cell, functional-genomic, proteomic, metabolomic, or imaging approaches to cancer and/or immunity
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biological system (i.e. DNA and protein sequences). Interprets data analysis of high throughput genomics, proteomics and genetic data. Performs other related work as needed. Minimum Qualifications Education