Bioinformatics Analyst III (Target Identification) at US Tech Solutions, Inc.

Duration: 6 months contract

Job Description:

• We are seeking a Bioinformatics Scientist to join our cross-functional team and provide advanced computational biology support to aid genetic-data-driven target discovery for male-pattern baldness.
• The successful candidate will use integrated approaches involving a variety of ‘ omics data to test and refine biological hypotheses in coordination with wet-lab and computational colleagues.
• Applicants should be proficient with advanced transcriptomic data analysis in R, including relevant bioinformatics packages (e.g., Seurat, limma).
• Those with experience integrating multi-modal data (e.g., scRNAseq + scATACseq, single-cell RNAseq + spatial proteomics) and/or incorporating genetic evidence in causal gene discovery are especially encouraged to apply.

Responsibilities:

• transcriptomic data analysis, including bulk, single-cell, and/or spatial transcriptomic and CRISPR data (e.g., cell type annotation, differential gene expression analysis, gene set enrichment analysis, advanced results visualization, and result interpretation)
• multiomic data integration to advance data-driven target prioritization strategy

Experience:

• PhD preferred , would look at Masters with 5+ years of experience
• Transcriptomic data analysis , including bulk, single-cell, and/or spatial transcriptomic and CRISPR data (e.g., cell type annotation, differential gene expression analysis, gene set enrichment analysis , advanced results visualization, and result interpretation)
• Multiomic data integration to advance data-driven target prioritization strategy
• Applicants should be proficient with advanced transcriptomic data analysis in R, including relevant bioinformatics packages (e.g., Seurat, limma).
• Those with experience integrating multi-modal data (e.g., scRNAseq + scATACseq, single-cell RNAseq + spatial proteomics) and/or incorporating genetic evidence in causal gene discovery are especially encouraged to apply.

Skills:

• Multiomic data integration to advance data-driven target prioritization strategy
• Applicants should be proficient with advanced transcriptomic data analysis in R, including relevant bioinformatics packages (e.g., Seurat, limma).

Education:

• PhD preferred , would look at Masters with 5+ years of experience