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from multiple cancer types. Clinico-genomic infrastructure & modeling - Establish a comprehensive clinico-genomic database, web resource, and information hub for rare pediatric and adult cancers; develop
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. The project examines how the Partnership Model is implemented across districts and schools, how well it aligns with local needs, and whether it supports improvements in student-, educator-, and system-level
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) Demonstrated proficiency in R and/or Python for genomic data analysis Experience with next-generation sequencing data analysis (RNA-seq, ATAC-seq, ChIP-seq, or equivalent) Ability to work independently and
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apply advanced approaches in mammalian sleep neurobiology, neurogenetics, molecular biology, RNA sequencing, FACS, biochemistry, confocal imaging, behavioral neuroscience, and multi-omic data analysis
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Qualifications* Prior experience with mammalian tissue culture, DNA/RNA molecular assays, protein biology, high-throughput genetic screens, and -omics datasets is desired Prior experience with sequencing data
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, cell culture, RNA isolation, Western blotting, CRISPR editing, transfection, and advanced microscopy are expected. Familiarity with techniques such as RNA-sequencing, RNA silencing techniques, ELISA and
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, generating, analyzing and interpretating environmental health data, and preparing manuscripts and other scholarly products. Research topics can be proposed by the fellow and should be aligned with interests
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recommendations for climate resiliency and soil sustainability, and assessing human and animal health associated with emerging contaminants, such as PFAS. OASR actively interacts with multiple local, state, and
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the research the applicant wishes to conduct while in residence. The proposal must address challenges or opportunities at the intersection of social/environmental sustainability and business/markets and align
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Apply Now Responsibilities* The successful candidate would work on multiple projects all related to modeling the function of the human auditory system. Responses to both natural stimuli (like speech