The Biostatistician in Biostatistics (Early Development) is responsible for supporting Discovery and Research, and Experimental Medicine Biostatistics functions. Ideal candidate for this position should be experienced in the design and analysis of high dimensional image and –omics data, and familiar with recent developments in statistical sciences, specifically in the areas of pattern recognition, multiple testing, predictive models with variable selection, clustering and classification, nonparametric methods, resampling and small sample methods. A thorough understanding of biological systems is important.
Candidate should possess excellent client interface capability, including good communication and writing skills, exceptional problem solving skills requiring creative thinking and rigorous planning.
Experience with both scientific and clinical biomarker studies is highly desirable and candidate should be skilled in the use of popular software for analyzing high dimensional image and –omics data.
Responsibilities include consulting, problem solving, and analytic support for research scientists in the drug discovery, biomarkers (imaging, genetic, genomic, proteomic, epigenetic and cytokines) and pre-clinical setting.
Managing large data, both in-house data and public data.
PhD with 1-3 years experience in early development and/or biomarker studies. Post-doctoral experience in an academic environment with high-dimensional data analysis is also acceptable.
Experience with biomarker studies and high dimensional data
Skilled in one or more of software such as Plink, R/Bioconductor, SPM, SCORE-seq, PennCNV, GSEA, etc.
PhD Biostatistics, Applied Mathematics, or Statistics.
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