The Genomics Research Center (GRC) is a center of excellence for genetics and genomics that supports both Discovery and Development. The GRC plays an integral role towards our goal of developing world class genetics and genomics research, focusing on finding the right targets and helping us better understand not only human disease biology but also the behavior of and response to our drugs in clinical trials. Within the GRC, the Department of Bioinformatics is responsible for data analysis and provides analytical insight for both internal and external data. This involves the identification and characterization of underlying genetic, epigenetic, or genomic factors that are associated with disease diagnosis, prognosis and response (efficacy and safety) to drug treatment, identification of new targets, and interpretation of the impact of genetic and genomic evidence from population-based studies. We have an exciting opportunity for a bioinformatic/Data scientist, based in Cambridge Massachusetts. The candidate will work closely with computational biologists and research project teams in Immunology based in Cambridge (MA), North Chicago (IL) to support analyzing genetics and single cell and multi-omics datasets to derive insights into immunological diseases, identify novel therapeutic targets and biomarkers specific to patient cohorts and Abbvie pipeline drugs.
Key Responsibilities:
Collaborate with research & clinical scientists to systematically identify and internalize molecular data and knowledge base that are relevant to Abbvie immunology drug discovery.
Execute bioinformatics analysis using genetics, bulk and single cell transcriptomics and proteomics data in combination with phenotypic data.
Apply, refine, and extend established workflows for data analysis and visualization.
Generate static and interactive data visualization (e.g. R shiny apps) based on individual or combined datasets.
Communicate analytical approach and results verbally and in writing for scientific and technical audiences.
Qualifications
Position will be hired based on level of education and experience.
Bachelors or Masters degree in quantitative sciences (mathematics, computer science, statistics, bioinformatics, bioengineering) with typically 2+(MS) or 5+(BA) years of working/ project experience on biological data or biological sciences with demonstrated skills in informatic analyses.
Hands on experience in biological data and knowledge integration. Immunological focus is a plus but not required.
Highly proficient with statistical and programing languages (Java, Python, Perl, R), Unix/Linux/cloud environment, and SQL and noSQL database query languages.
Proficiency in collaborative coding environments (GitHub) and automating computational work in environments such as jupyter or R markdown.
Experience with constructing and running analytical workflows is desired.
Experience with visualization tools and libraries such as R-shiny, D3, and web development is preferred.
Experience in genetic and/or epigenetic data analyses using existing or custom pipelines is preferred
Experience with text mining techniques (e.g. regular expression) is desired.
Ability to work in a multiple-task, fast-paced, highly collaborative and dynamic work environment.
A self-motivated learner and thinker.
An analytical mind with outstanding interpersonal, verbal and written communication skills.
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