<p>Bioinformatics Scientist Job ID: 25-09142</p> <p>Job Title: Bioinformatics Scientist</p> <p>Duration: 23 months, 40 hrs / week</p> <p>Location: Cambridge, MA 02141</p> <p>Required Qualifications:</p> <ul> <li>Ph.D. in Computational Biology or a related field. </li><li>A proven track record of over 5 years in multi-omics analysis. </li><li>Fundamental understanding of statistical methods and multi-omics data analysis and integration (e.g., RNA-Seq, single-cell RNA-Seq, genotype, spatial transcriptomics, OLINK). </li><li>Proficiency in R, Python, and Bash, with the ability to establish best practices for reproducible data analyses. </li><li>Experience with high-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets). </li><li>A collaborative and self-motivated individual with a strong work ethic, capable of managing multiple objectives in a dynamic environment and adapting to changing priorities. </li><li>Excellent written and verbal communication skills. </li></ul> <p>Preferred Qualifications:</p> <ul> <li>Experience in processing and analyzing real-world data. </li><li>Familiarity with spatial transcriptomics analysis. </li><li>Knowledge of statistical and population genetics principles. </li></ul> <p>Key Skills:</p> <ul> <li>Required expertise with multi-omics data analysis and integration (e.g., RNA-Seq, single-cell RNA-Seq. </li><li>Transcriptomics analysis. </li><li>Proficiency in R and Bash. </li><li>High-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets). </li></ul> <p>Responsibilities:</p> <p>Key Responsibilities:</p> <ul> <li>Data Ingestion: Query external databases to acquire relevant multi-omics datasets (e.g., PubMed, Gene Expression Omnibus, ArrayExpress, gnomAD, GTEx, Ensembl). </li><li>RNA-seq Analysis: Perform quality control (QC) and analysis of bulk and single-cell RNA-seq data using state-of-the-art methods (e.g., FastQC, STAR, Limma, DESeq2, clusterProfiler, Seurat, scanpy, LeafCutter). </li><li>Multi-Omics Analysis: Analyze diverse molecular data types including spatial transcriptomics (e.g., Slide-seq, MERFISH, squidpy) and proteomics (e.g., OLINK, mass spectrometry-based approaches). </li><li>Data Integration: Integrate multi-omics datasets, including gene/protein expression, mRNA splicing, spatial transcriptomics, and genotype data. </li><li>Documentation: Prepare detailed documentation of analysis methods and results in a timely manner. </li><li>Job details </li><li></li></ul>