Senior Bioinformatics Scientist - III

Job Title: Senior Bioinformatics Scientist - III
Job Location: Cambridge, MA 02141
Job Duration: 24+ Months (Possibilities of Extension)

Pay rate: $100.50/Hour on W2
 
Job Description:
The Precision Genetics group within the Data and Genome Sciences Department is seeking a skilled Contractor to join our Computational Precision Immunology team. We focus on multi-modal and multi-scale data analyses to drive innovative research in precision genetics.
 
Key Responsibilities:

• Data Ingestion:
  Query external databases such as PubMed, Gene Expression Omnibus, ArrayExpress, gnomAD, GTEx, and Ensembl to acquire relevant multi-omics datasets.
• RNA-seq Analysis:
  Perform quality control (QC) and analysis of bulk and single-cell RNA-seq data using tools like FastQC, STAR, Limma, DESeq2, clusterProfiler, Seurat, scanpy, and 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:

• Ph.D. in Computational Biology or a related field.
• 5+ years of experience in multi-omics analysis.
• Strong understanding of statistical methods and multi-omics data analysis/integration (e.g., RNA-Seq, single-cell RNA-Seq, genotype, spatial transcriptomics, OLINK).
• Proficiency in R, Python, and Bash; ability to implement best practices for reproducible data analyses.
• Experience with high-performance computing (HPC) systems and AWS Cloud Computing (IAM, S3 buckets).
• Collaborative, self-motivated, strong work ethic, ability to manage multiple priorities in a dynamic environment.
• Excellent written and verbal communication skills.

 
Preferred Qualifications:

• Experience with real-world data processing and analysis.
• Familiarity with spatial transcriptomics data analysis.
• Knowledge of statistical and population genetics principles.

 
Key Skills:

• Expertise in multi-omics data analysis and integration (RNA-Seq, single-cell RNA-Seq).
• Transcriptomics analysis.
• Proficiency in R and Bash scripting.
• Experience with HPC systems and AWS Cloud (IAM, S3).

#sczr2