Utilize off-the-shelf and develop bespoke statistical methods to uncover meaningful and actionable scientific findings from omics data (e.g., genomics, transcriptomics, epigenomics, proteomics) from internal clinical and translational activities and from relevant external studies; Partner with clinical development and translational science teams to address key project team questions related to biomarker strategy, drug mechanisms of action, disease subtypes, indication selection, patient stratification, etc, with the appropriate experimental design, analytical approaches, and statistically meaningful results; Conduct necessary quality control checks and data management of large omics and phenotypic datasets; Establish, review and improve relevant computational pipelines, workflows and methodologies; Communicate analytical approach and results verbally and in writing for scientific and technical audiences; Provide expertise and technical consultation for external collaborations/partnerships in academia and industry
Requirements:
PhD, MS or BS in bioinformatics, statistics, mathematics, computer science, computational biology, genomics, or a related field with typically 0+ (PhD), 4-6+ (MS), or 6-8+ (BS) years of experience; Hands on experience in statistical analysis of multi-omics data (e.g. bulk/single-cell RNA-seq, microarray, proteomics or genetics data), longitudinal data, and developing predictive models; Demonstrated ability to provide expertise in state-of-the art statistical methods for differential expression and pathway analysis; Strong verbal and written communication skills, with the ability to effectively convey complex concepts to a diverse group of individuals including computational experts and medical professionals; Fluency in statistical and programing languages (R, Python), Unix/Linux/cloud environment, and SQL and noSQL database query languages
Text:
Senior Scientist I, Immunology Computational Biology Utilize off-the-shelf and develop bespoke statistical methods to uncover meaningful and actionable scientific findings from omics data (e.g., genomics, transcriptomics, epigenomics, proteomics) from internal clinical and translational activities and from relevant external studies; Partner with clinical development and translational science teams to address key project team questions related to biomarker strategy, drug mechanisms of action, disease subtypes, indication selection, patient stratification, etc, with the appropriate experimental design, analytical approaches, and statistically meaningful results; Conduct necessary quality control checks and data management of large omics and phenotypic datasets; Establish, review and improve relevant computational pipelines, workflows and methodologies; Communicate analytical approach and results verbally and in writing for scientific and technical audiences; Provide expertise and technical consultation for external collaborations/partnerships in academia and industry PhD, MS or BS in bioinformatics, statistics, mathematics, computer science, computational biology, genomics, or a related field with typically 0+ (PhD), 4-6+ (MS), or 6-8+ (BS) years of experience; Hands on experience in statistical analysis of multi-omics data (e.g. bulk/single-cell RNA-seq, microarray, proteomics or genetics data), longitudinal data, and developing predictive models; Demonstrated ability to provide expertise in state-of-the art statistical methods for differential expression and pathway analysis; Strong verbal and written communication skills, with the ability to effectively convey complex concepts to a diverse group of individuals including computational experts and medical professionals; Fluency in statistical and programing languages (R, Python), Unix/Linux/cloud environment, and SQL and noSQL database query languages
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