

Bioinformatics Scientist (multi-omics)
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Bioinformatics Scientist (multi-omics) on a 23-month contract in Cambridge, MA, offering $50.00 to $77.53 hourly. Requires a Ph.D. and 3+ years in multi-omics analysis, proficiency in R, Python, Bash, and experience with HPC and AWS.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
616
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ποΈ - Date discovered
June 11, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
On-site
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Cambridge, MA
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π§ - Skills detailed
#Data Integration #Documentation #Data Science #AWS (Amazon Web Services) #Python #Datasets #S3 (Amazon Simple Storage Service) #Cloud #R #Databases #Bash #Data Analysis #IAM (Identity and Access Management) #Data Ingestion
Role description
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Details:
β’ Pay for this position is 50.00 to 77.53 hourly depending on experience.
β’ This position is a 23-month contract
β’ Location: Cambridge, MA (100% onsite)
Qualifications:
β’ Ph.D. in Computational Biology or a related field is required.
β’ A proven track record of over 3 years in multi-omics analysis (can be academic).
β’ Fundamental understanding of statistical methods and multi-omics data analysis and integration (e.g., RNA-Seq, single-cell RNA-Seq, genotype, spatial transcriptomics, OLINK).
β’ Proficiency in R, Python, and Bash, with the ability to establish best practices for reproducible data analyses.
β’ Experience with high-performance computing (HPC) systems and AWS Cloud Computing (e.g., IAM, S3 buckets).
β’ 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.
β’ Excellent written and verbal communication skills.
Responsibilities:
β’ The Precision Genetics group within the Data and Genome Sciences Department is seeking a skilled Contractor to join our Computational Precision Immunology team.
β’ 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.
β’ Data Ingestion: Query external databases to acquire relevant multi-omics datasets (e.g., PubMed, Gene Expression Omnibus, ArrayExpress, gnomAD, GTEx, Ensembl).
β’ 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).
β’ 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).
β’ Data Integration: Integrate multi-omics datasets, including gene/protein expression, mRNA splicing, spatial transcriptomics, and genotype data.
β’ Documentation: Prepare detailed documentation of analysis methods and results in a timely manner.