Requirements

Experience with high content data analysis, such as RNA sequencing, whole genome sequencing, and proteomic data is required.
Statistical skills and experience with large datasets (gene expression, proteomic data, and next-generation sequencing), predictive models and diagnostics, network analysis, and clinical trial data are required.
The candidate must have a current knowledge of the bioinformatics scientific literature (especially for RNA sequencing) and strong communication skills.
Ability to perform data quality control and interface with internal wet laboratory to ensure quality and compliance with appropriate internal policies is required.
Proficiency in standard analytical platforms (e.g., R, MATLAB) as well as gene set enrichment and pathway analysis software tools (e.g., GSEA/GSVA, Thomson Reuters GeneGo, Ingenuity, Cytoscape, etc.) is required.
Programming skills in Python are highly desired.
Strong communication (written and oral presentation) and organization skills, and ability to handle multiple projects simultaneously are essential.
Expertise in predictive algorithms and experience in biomarker discovery and/or co-diagnostic development for pharmaceutical applications is preferred.

Responsibilities

Analyze high content data such as RNA sequencing, whole genome sequencing, and proteomic data.
Perform data quality control and interface with internal wet laboratory to ensure quality and compliance with internal policies.
Apply statistical methods to large datasets including gene expression, proteomic data, and next-generation sequencing; develop and validate predictive models and diagnostics, perform network analysis, and work with clinical trial data.
Utilize standard analytical platforms (R, MATLAB) and gene set enrichment and pathway analysis tools (GSEA/GSVA, Thomson Reuters GeneGo, Ingenuity, Cytoscape) for data analysis.
Develop and apply predictive algorithms and contribute to biomarker discovery and/or co-diagnostic development for pharmaceutical applications.

Desired Qualifications

Familiarity with human translational research, clinical trial metadata, and experience with predictive models and diagnostics is a plus.
Programming in Python is highly desired.
Expertise in predictive algorithms and experience in biomarker discovery and/or co-diagnostic development for pharmaceutical applications is preferred.
MS in Bioinformatics or at least 3 years of experience in Computational Biology, Immunology, Statistics, Network Pharmacology / Systems Biology, Bioinformatics or related field. PhD is preferred.

Scientist 2

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