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The laboratory of Dr. Michael Green is focused on understanding the molecular etiology of B-cell lymphoma and aims to use this knowledge to identify novel therapeutic strategies. Our laboratory employs high-throughput genomics to interrogate primary tumor specimens and transgenic mouse models; including whole-genome/exome sequencing, RNA-seq, ChIP-seq, CUT&RUN and ATAC-seq, as well as cutting-edge single cell approaches. This position will focus on the integration and analysis of single cell RNA-sequencing and DNA sequencing datasets from lymphoma and myeloma patient's treated with CAR T-cells and other biologics, as a progression and expansion of our recent workLEARNING OBJECTIVESExperience working in high-performance computing cluster environment, experience working with single cell RNA/ATAC, ChIP-seq, ATAC-seq, Hi-C, or other large-scale epigenomics data analysis is highly preferred. A good understanding of cancer biology, cell signaling pathways, or drug response mechanisms is also preferred.ELIGIBILITY REQUIREMENTSIndividuals with a PhD degree in computational biology, bioinformatics, genomics, genome science or a related field are encouraged to apply. A strong computational background, proficiency in at least one programming language (e.g., R, Python, Perl, C, Java) and knowledge of biostatistics are required.FACULTY MENTORDr. Michael Green
Full-time