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cancer genomics resources and databases, including The Cancer Genome Atlas, cBioPortal, Genomic Data Commons, dbGaP, GEO, and related resources. Experience with high-performance computing, cloud-based
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benefits will be offered based on the NIH postdoctoral pay scale. The candidate will be expected to attend and present at local and national scientific meetings, and funds are available for travel. Create a
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nanoparticle platform development for DNA delivery; mRNA-based non-viral cancer immunogene therapy; and lipid nanoparticle platform development for inhalable mRNA delivery. The candidate will plan, design and
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, glial, and immune cell culture, nucleic acid extractions, ELISAs, bead-based microarrays, immunohistochemistry, spatial transcriptomics, and molecular analyses. The candidate will summarize research data
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antibody–antigen interactions in cancer and viral diseases, with the goal of advancing therapeutic and vaccine design. The successful candidate will lead structure-based studies of glycoproteins, antibodies
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may be assigned based on needs of ongoing and new research projects. Minimum Education and Experience Requirements PhD or equivalent degree in Health Management and Policy, Health Services or related
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. The experimental work is supported by first-principles based transport modeling, and the broader collaborative network includes materials synthesis experts at Ohio State University, as well as collaborators
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. The scholar will perform computational and laboratory-based research to investigate viral deactivation under varying environmental conditions. This position will contribute to data analysis, experimental design
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computing, cloud-based computing environments, workflow-management systems, containers, and/or software development practices. Experience with machine learning, predictive modeling, or artificial intelligence
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Education: PhD in Chemical Engineering or related field Desired Experience: 3 years of prior research experience on multiscale modeling, hybrid modeling, and model-based control or related fields. Additional