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Field
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for developing and using systems to phenotype root systems in greenhouse and field settings under the guidance of research mentors. Build skills in root image processing and other data analysis activities using
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apply them to cutting-edge single-cell datasets generated within the lab and from public resources. There is significant scope to shape the project around your interests, including live-cell imaging, flow
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transcriptomics or proteomics, multiplexed imaging and/or integration of spatial transcriptomics with single-cell RNA-sequencing datasets. Experience from relevant research projects will be considered an advantage
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to cancer progression. Using image-based siRNA screens, we have identified novel regulators of ER-phagy. This project aims to investigate the molecular mechanisms of ER-phagy and how this contributes
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for medical imaging, precision medicine, statistical genomics, graphical models, and the analysis and integration of complex, high-dimensional biomedical data. The fellow will be expected to develop novel
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humane endpoints. Collect blood, tumors, and other tissues; perform or coordinate necropsy and tissue processing; and support downstream histologic, molecular, and pharmacodynamic/target-engagement
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field high-speed microscopic imaging Experience with control and synchronization of high-speed imaging and lighting systems Experience with image post-processing and data extraction Personal
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. Work collaboratively with multidisciplinary teams across materials, mechanical, and electrical engineering. Conduct laboratory experiments and support prototype development, contributing to system-level
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, with desirable skills including building or aligning bespoke systems. Strong programming and data-analysis skills (e.g. Python and/or MATLAB) for processing signals and imaging data. The ability
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, including genomic, transcriptomic, epigenomic, proteomic, metabolomic, and circulating biomarker data derived from patient tissues and liquid biopsies. Our goal is to characterize the molecular processes