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computing environments. Experience with single cell sequencing or spatial omics data strongly preferred. Strong publication record and written communication skills. Desired Qualifications* Expert in graph
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single cell sequencing or spatial omics data strongly preferred. Strong publication record and written communication skills. Desired Qualifications* Expert in graph based, multiple instance learning, large
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, and advanced sequencing technologies to generate large-scale datasets. In parallel, you will develop and apply computational pipelines that integrate sequence analysis, structural modeling, and
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poorly annotated. This is primarily due to their small size and repetitive nature that results in difficulties in sequencing and assembly. In the last three years, USDA-ARS has invested significantly in
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, motivated early-career researcher interested in learning to collect, manage, analyze, and interpret data from multiple systems including mobile eye tracking, motion capture, and force plate posturography as
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(http://vanallenlab.dana-farber.org/) to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts
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, and publication list In your cover letter, please explicitly detail your experience with genomic and transcriptomic approaches, highlighting how your skills align with the research focus
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: · Perform collaborative research with multiple faculty members at ARDMRI on projects involving genomics data analysis using single cell RNA-seq, CHIP-seq/ATAC-seq, spatial transcriptomics, HiC/HiCHIP, RIBO
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manuscript writing. Additionally, pre-planning projects, RNA isolation, quality control, qPCR, protein assays and quantification, Western Blot, cell culture, single cell and next-gen sequencing experiments
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and (bio)statistics, biology or medicine. Applicants must have a proven publication record. Prior experience with handling massively parallel sequencing data is considered an advantage. Postdocs will