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quantify high-throughput binding data. Examples of suitable backgrounds: Optical engineering, hardware-software integration, image analysis. Building quantitative models: Using high-throughput binding data
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different conditions using existing software (written in Fortran). Analysis of data using quantitative genetics tools (e.g., calculation and comparison of genetic and phenotypic covariance matrices
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the development team of TreePPL (www.treeppl.org ), a universal probabilistic programming language and new software for phylogenetics. The successful candidate will be responsible for the user-interface aspects
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