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Position: Associate Computational Biologist
Institution: Dana-Farber Cancer Institute
Location: Boston, Massachusetts, United States
Duties: The Kadoch lab uses multidisciplinary approaches including biochemistry, biophysics, structural biology, chemical biology, and functional genomics and epigenomics to explore the mechanisms of chromatin remodeling complexes, which are among the most frequently mutated cellular entities in human cancers and other diseases. As such, our computationally-centered projects in the lab are highly diverse and involve extensive genomics (i.e. analysis of many NGS methods including DNA sequencing, RNA sequencing (RNA-seq), ATAC-seq, ChIP-seq, CUT&RUN, CUT&TAG, single-cell ATAC+RNA-seq, among other approaches), analysis of functional screening datasets (i.e. genome-wide as well as targeted CRISPR- and base editing-based screens for cell fitness or other cellular outcomes), 3D structural biology (i.e. use of Pymol and UCSF Chimera for structural analysis
Requirements: BA/BS degree required. The successful applicant will have coding experience (i.e. in R, Python, or other languages) relevant to bioinformatics/computational biology, familiarity with working in a Unix environment and use of SLURM or similar job scheduler (high performance computing), working knowledge of genomic technologies and bioinformatic processes and/or structural biology, ability to both implement and develop new bioinformatic pipelines in shell scripts
   
Text: Associate Computational Biologist The Kadoch lab uses multidisciplinary approaches including biochemistry, biophysics, structural biology, chemical biology, and functional genomics and epigenomics to explore the mechanisms of chromatin remodeling complexes, which are among the most frequently mutated cellular entities in human cancers and other diseases. As such, our computationally-centered projects in the lab are highly diverse and involve extensive genomics (i.e. analysis of many NGS methods including DNA sequencing, RNA sequencing (RNA-seq), ATAC-seq, ChIP-seq, CUT&RUN, CUT&TAG, single-cell ATAC+RNA-seq, among other approaches), analysis of functional screening datasets (i.e. genome-wide as well as targeted CRISPR- and base editing-based screens for cell fitness or other cellular outcomes), 3D structural biology (i.e. use of Pymol and UCSF Chimera for structural analysis BA/BS degree required. The successful applicant will have coding experience (i.e. in R, Python, or other languages) relevant to bioinformatics/computational biology, familiarity with working in a Unix environment and use of SLURM or similar job scheduler (high performance computing), working knowledge of genomic technologies and bioinformatic processes and/or structural biology, ability to both implement and develop new bioinformatic pipelines in shell scripts
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