Associate Bioinformatics Scientist – II

Cambridge, Massachusetts
July 23, 2025
$78 / hour
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Job Description

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.

Duties and Responsibilities:

Data Ingestion:

  • Query external databases to acquire relevant multi-omics datasets (e.g., 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 (e.g., FastQC, STAR, Limma, DESeq2, clusterProfiler, Seurat, scanpy, LeafCutter).

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).

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.

Education and Experience:

  • Ph.D. in Computational Biology or a related field.
  • A proven track record of over 3 years in multi-omics analysis.
  • Experience with high-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).
  • Experience in processing and analyzing real-world data.

Knowledge, Skills and Abilities:

  • Fundamental understanding of statistical methods and multi-omics data analysis and integration (e.g., 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.
  • 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.
  • Familiarity with spatial transcriptomics analysis.
  • Knowledge of statistical and population genetics principles.

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