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Field
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. In vitro approaches include mammalian cell culture, molecular biology, microscopy, immunohistochemistry, functional genomics, proteomics, high throughput drug screening, and genome-wide sequencing. In
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immunity. The successful candidate will generate, analyze, and integrate multi-omics microbiome datasets, including shotgun metagenomics, 16S rRNA sequencing, single-cell transcriptomics, and proteomics
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/~wwang7 . Position Title: Postdoctoral Fellow in Cancer Computational Biology Program/Position Description: Analyze next-generation sequencing (NGS) data, including: Develop computational and statistical
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Description: Key Roles and Responsibilities: Research Overview: Develop and perform synthesis of multiple small molecule platforms in collaboration with principal investigators of KUMC, KUCC and from other
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are not limited to cell culture, ELISA, RT-qPCR, flow-cytometry, sequencing and analytical biochemistry techniques. Training will be provided in all techniques but individuals with laboratory experience in
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COMPUTATIONAL BIOLOGIST FELLOW to lead cutting-edge studies of genetic risk for cancer using large-scale multimodal sequencing datasets across tens of thousands of individuals. The main objective of these studies
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, specialized research training. Through the mentorship from our committed faculty, Fellows will gain invaluable experience leading novel projects that align with their area(s) of interest and help to support
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Research Associate, Translational Research Fellow - Dept. Ophthalmology Visual & Anatomical Sciences
and application, CRISPR/Cas mutagenesis, and single-cell RNA sequencing is highly preferred. Proficiency with relevant data analysis and visualization tools (e.g., R, MATLAB, or Python) is required
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from Washington, D.C., George Mason University is uniquely positioned for collaborations with multiple academic institutions, government laboratories, and industry partners in the D.C.–Maryland–Virginia
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. Strong fundamentals in cancer biology and statistics are essential. Demonstrated proficiency in multiple programming languages such as Python/R, with experience in computational analysis of omics datasets