Bioinformatics Scientist III Senior

Position Title: Bioinformatics Scientist - III (Senior)

Work Location: Cambridge, MA 02141

Assignment Duration: 23 months

Work Schedule: 8-5 M-F

Work Arrangement: Onsite

Position Summary: The Precision Genetics group within the Data and Genome Sciences Department is seeking a skilled Contractor to join our Computational Precision Immunology team.

Background & Context:

* 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 (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.

Qualification & Experience:

* Ph.D. in Computational Biology or a related field.

* A proven track record of over 5 years in multi-omics analysis.

* 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.

* Experience with high-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 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: Experience in processing and analyzing real-world data.

* Preferred: Familiarity with spatial transcriptomics analysis.

* Preferred: Knowledge of statistical and population genetics principles.