Title: Bioinformatics Scientist - III
Location: Cambridge, MA
Contract Duration: Months
Pay Range: $ - $ USD hourly on W
Job Summary:
The Precision Genetics group within the Data and Genome Sciences Department is seeking a skilled Contractor to join our Computational Precision Immunology team. We are looking for a data scientist with extensive experience in multi-modal and multi-scale data analyses to contribute to our innovative research efforts.
Key Responsibilities:
• Data Ingestion: Query external databases to acquire relevant multi-omics datasets (, PubMed, Gene Expression Omnibus, ArrayExpress, gnomAD, GTEx, Ensembl).
• RNA-seq Analysis: Perform quality control (QC) and analysis of bulk and single-cell RNA-seq data using state-of-the-art methods (, FastQC, STAR, Limma, DESeq, clusterProfiler, Seurat, scanpy, LeafCutter).
• Multi-Omics Analysis: Analyze diverse molecular data types including spatial transcriptomics (, Slide-seq, MERFISH, squidpy) and proteomics (, OLINK, mass spectrometry-based approaches).
• Data Integration: Integrate multi-omics datasets, including gene/protein expression, mRNA splicing, spatial transcriptomics, and genotype data.
• Documentation: Prepare detailed documentation of analysis methods and results in a timely manner.
Required Qualifications:
• in Computational Biology or a related field.
• A proven track record of over years in multi-omics analysis.
• Fundamental understanding of statistical methods and multi-omics data analysis and integration (, RNA-Seq, single-cell RNA-Seq, genotype, spatial transcriptomics, OLINK).
• Proficiency in R, Python, and Bash, with the ability to establish best practices for reproducible data analyses.
• Experience with high-performance computing (HPC) systems and AWS Cloud Computing (, IAM, S buckets).
• 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.
• Excellent written and verbal communication skills.
Preferred Qualifications:
• Experience in processing and analyzing real-world data.
• Familiarity with spatial transcriptomics analysis.
• Knowledge of statistical and population genetics principles.
Note:
• Onsite role at Cambridge, MA.
• Do not submit candidates who are looking for remote.
• Do not submit candidates with just BS/MS.
Key Skills:
• Required expertise with multi-omics data analysis and integration (, RNA-Seq, single-cell RNA-Seq.
• Transcriptomics analysis.
• Proficiency in R and Bash.
• High-performance computing (HPC) systems and AWS Cloud Computing (, IAM, S buckets).