Solutions and software architect of the omics data generatedPipeline development and optimizationIntegration of software tools for easy access for scientistsStatistical data analysis Data visualization for big omics datasetsAnalysis of next-generation sequencing datasets.Predictive models be developed as useful in Genomic Selection (gBLUP, EGBLUP, Bayesian statistics, random forest, gradient boosting, deep neural networks)GWAS and post-GWAS analysis for the identification of candidate genes using multi-omics datasets and systemic gene interaction networksR | Python | Perl | Julia

Next-generation sequencing data analysis (GBS, mRNA-seq, small RNA-seq)Population genetics analysis for the diverse pool of germplasmQuantitative genetics and statistical methods to identify the association of SVs to traits.R programming for statistical analysis of dataPERL and BASH programming for automation of batch processing