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Intelliswift - An LTTS CompanyCambridge, MA, United States
6 days ago
Job type
Full-time
Job description
Job Title : Bioinformatics Scientist
Duration : 23 months, 40 hrs / week
Location : Cambridge, MA 02141
Required Qualifications :
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 Qualifications :
Experience in processing and analyzing real-world data.
Familiarity with spatial transcriptomics analysis.
Knowledge of statistical and population genetics principles.
Key Skills :
Required expertise with multi-omics data analysis and integration (e.g., RNA-Seq, single-cell RNA-Seq.
Transcriptomics analysis.
Proficiency in R and Bash.
High-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).
Responsibilities :
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.
Key Skills :
Required expertise with multi-omics data analysis and integration (e.g., RNA-Seq, single-cell RNA-Seq.
Transcriptomics analysis.
Proficiency in R and Bash.
High-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).