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for high-dimensional dependent data, and data sketching approaches for massive data. Opportunities to Contribute: Develop statistical/machine learning methodology for multi-modal imaging data integration
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Models: Perform microsurgeries and longitudinal studies using small animal models of myocardial infarction or heart failure to evaluate therapeutic outcomes. Data Acquisition: Utilize advanced imaging (e.g
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learned to support reproducibility and future research activities. Support the integration of research outcomes into prototype systems, operational demonstrations, or technology transition activities
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/Resume to assist us with the review process. You may upload these documents on the application under CV/Resume. Responsibilities Research Under general supervision, is responsible for conducting research
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supervision, this position is responsible for conducting multi-proxy analyses of legacy Antarctic sediment cores housed at the Gulf Coast Repository, including sedimentological, geochemical, and imaging-based
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Substantial published experience with PET imaging analysis. Experience with EEG data analysis or digital signal processing. Working knowledge of scientific computing languages, including Matlab, Python
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travel. Please note: This position is grant funded; future employment may be contingent upon future funding. Apply! Submitting a cover letter, resume/CV to assist us with the review process. You may upload
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biochemical, cell-based, immunologic, imaging, and/or computational assays as appropriate to project goals, including assay-development and drug-discovery workflows. Analyzes research data, summarizes results
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, imaging-probe chemistry, or diagnostic/point-of-care technology development. Experience with reagent formulation, stability testing, lyophilization, or development of assays for field or resource-limited
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funded; future employment may be contingent upon future funding. Apply! Submitting a cover letter, resume/CV to assist us with the review process. You may upload these documents to the application under CV