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methods (e.g., fluorescence, reflectance, or label-free modalities). Collaborate on development and optimization of imaging instrumentation and workflows. Perform tissue preparation, imaging, and data
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research approaches. Working closely with nursing partners and clinical collaborators, our exciting work combines non-invasive imaging technologies, deep learning, computer vision, and clinical workflow
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publications, is strongly preferred. PLEASE PROVIDE: A cover letter describing research interests, relevant experience, and career goals. Curriculum vitae, including a list of publications. Contact information
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, or multi-modal learning that integrates structured EHR and biomarker data. The fellow will have access to curated oncology datasets, high-performance computing infrastructure, and mentorship from a cross
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‑spectroscopy microscopes housed in the CPMM core facilities. Collaborate closely with CPMM teams across partner institutions and companies; share reagents, data, and expertise to drive center‑wide milestones
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of understanding how these processes influence development and disease states. The selected candidate will design and conduct experiments, analyze data, and contribute to scholarly publications while developing