

Computational Biologist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Computational Biologist on a 12-month hybrid contract in Pearl River, NY, with a pay rate of $38-$42.82/hr. Key skills include multi-omics data analysis, RNAseq technologies, and experience in vaccine or immunology research. Ph.D. required.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
336
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ποΈ - Date discovered
July 18, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Hybrid
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Pearl River, NY
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π§ - Skills detailed
#Databases #Data Science #Python #Linux #Visualization #AI (Artificial Intelligence) #ML (Machine Learning) #R #"ETL (Extract #Transform #Load)" #Cloud #Datasets #Data Analysis
Role description
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Job Title: Computational BiologistΒ (Hybrid)
Job Duration: 12 months contract
Location: Pearl River, NY 10965
Pay Range: $38-$42.82/ hr.
Hours: 8 AM-5 PM
Job Description:
POSITION SUMMARY
We are seeking a highly motivated contractor with a passion for using high-dimensional single cell immune profiling data in conjunction with innovative computational approaches and systems immunology knowledge to transforming vaccine research. Responsibilities will be developing analytical tools used for bulk RNAseq, single cell RNAseq, TCR sequencing, BCR sequencing, and host immune profiling. This role will integrate multi-omics data with preclinical/clinical data and provide scientific insights to immune responses elicited by vaccines or pathogens. This person will collaborate in a cross-functional teams and make strong impact to all stages of vaccine R&D.
Key Responsibilities:
β’ Integrate and analyze multi-omics datasets (e.g., transcriptomics, proteomics, metabolomics) to identify biomarkers and molecular signatures relevant to vaccine efficacy and safety.
β’ Familiar with state-of-art technology related to bulk RNAseq, single cell RNAseq, TCR profiling, and BCR profiling.
β’ Leverage public omics databases (e.g., GEO, ENCODE, UK Biobank, CELL×GENE) to support hypothesis generation and validation. Provides scientific insights to innate and adaptive immune responses induced by vaccines.
β’ Ability to handle single-cell data from raw data acquisition to data visualization and data analysis.
β’ Develop, document, and maintain reproducible computational pipelines and scripts using R and Python.
β’ Communicate complex data and results clearly to both technical and non-technical stakeholders. Collaborate extensively with those from other scientific disciplines from within the group, from other subdivisions of Vaccines R&D, from other divisions of client, and potentially from external partners.
Required Qualifications:
β’ Ph.D. in a relevant scientific field with a strong background in computational biology or bioinformatics.
β’ Extensive experience in analyzing multi-omics data (e.g., genetics, bulk RNA-seq, single-cell RNA-seq, spatial omics, proteomics, etc.) for biomedical research.
β’ Experience in biomarker discovery, particularly in the context of vaccine or immunology research.
β’ Familiarity with public omics databases and data repositories.
β’ Familiar with Linux environments, high-performance computing and/or cloud computing environment and broad experience with open-source bioinformatics tools to generate immunological insight.
β’ Strong communication and collaboration skills with the ability to work effectively in a hybrid team environment.
Preferred Qualifications:
β’ Extensive hand-on experience generating immunological insight from single cell sequencing data is highly desirable.
β’ Knowledge of machine learning techniques applied to biological data.
β’ Familiarity with artificial intelligence-empowered multimodal foundation models such as scGPT, UCE, scFoundation, Mal-ID
β’ Strong organizational skills and attention to detail in managing multiple projects and deadlines.
β’ Ability to document code thoroughly to ensure reproducibility and clarity for collaborative projects.
Hard Skills:
1. Integrate and analyze multi-omics datasets (e.g., transcriptomics, proteomics, metabolomics) to identify biomarkers and molecular signatures relevant to vaccine efficacy and safety.
1. Familiar with state-of-art technology related to bulk RNAseq, single cell RNAseq, TCR profiling, and BCR profiling.
1. Leverage public omics databases (e.g., GEO, ENCODE, UK Biobank, CELL×GENE) to support hypothesis generation and validation. Provides scientific insights to innate and adaptive immune responses induced by vaccines.
Skill: 10X Single Cell, BCR TCR, Bioinformatics, Computational biology, data science, Next Generation Sequencing (NGS), transcriptomics, immunology, Vaccines, proteomics, and Genomics.
Interview Process:
Panel Interview Teams w/ Camera On