Build from existing biomarker data workplans - including CITE-seq, TCRseq, WES/RNAseq, flow cytometry, and multiplex cytokines - to deeply immunophenotype manufacturing, final TIL drug product, and on-treatment patient samples; Work hand-in-hand with Translational Medicine leadership to connect diverse datapoints across numerous biomarker assays; Formulate, test, and iterate on translational hypotheses; analyze data and draw conclusions to deliver a robust package of biomarker data and presentations; Derive mechanistic insights, drive reverse translation, and improve future cellular drug products
Requirements:
Ph.D. in genomics or immunology/oncology with experience/expertise in bioinformatics and quantitative sciences (computer science, math, statistics and engineering); Proficiency with database systems, querying languages (SQL, MySQL), statistical analysis in R or Python; Expertise in biomarker discovery, genomics, and multi-omics data visualization is highly preferred; Experience in collaborative development platforms, e.g. Git, and virtualized working environments, e.g. Docker, is preferred
Text:
Senior Scientist, Translational Medicine Data Science Build from existing biomarker data workplans - including CITE-seq, TCRseq, WES/RNAseq, flow cytometry, and multiplex cytokines - to deeply immunophenotype manufacturing, final TIL drug product, and on-treatment patient samples; Work hand-in-hand with Translational Medicine leadership to connect diverse datapoints across numerous biomarker assays; Formulate, test, and iterate on translational hypotheses; analyze data and draw conclusions to deliver a robust package of biomarker data and presentations; Derive mechanistic insights, drive reverse translation, and improve future cellular drug products Ph.D. in genomics or immunology/oncology with experience/expertise in bioinformatics and quantitative sciences (computer science, math, statistics and engineering); Proficiency with database systems, querying languages (SQL, MySQL), statistical analysis in R or Python; Expertise in biomarker discovery, genomics, and multi-omics data visualization is highly preferred; Experience in collaborative development platforms, e.g. Git, and virtualized working environments, e.g. Docker, is preferred
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