
Computational biologist with Ph.D degree in biology and six-years experience analyzing high-throughput sequencing data including single-cell RNA sequencing (scRNA-seq), spatial transcriptomics and bulk RNA sequencing. Strong coding skills in R ,Python and Linux shell for data wrangling, normalization, analysis and visualization with solid background in biology and biostatistics principles. Looking for a bioinformatics analyst position to contribute my skills and expertise in molecular biology and computer science to cancer research.
Experience of high-throughput sequencing data analysis, including single-cell RNA-seq, spatial transcriptomics, RNA-seq, ChIP-seq, WGS
Proficient in Linux/UNIX systems, shell scripting and work with High-Performance Computing clusters
Strong coding skills in R and python including data analysis and visualization
Experience of developing data visualization and mining tool using Shiny
Experienced in GWAS analysis using TASSEL pipeline and GAPIT package
Familiarity with statistical methodologies such as ANOVA, generalized and/or linear mixed models, correlation analysis and principle component analysis (PCA)
Experienced in Git version control systems and container related tools (Docker)
Excellent communication skills and the ability to work constructively within a team environment
Microsoft Office Suite, Illustrator, Photoshop, Origin, Endnote
Genomic DNA/cDNA quantification with real-time PCR methods
Early Career Researcher Awards, La Trobe University, 2021.
Project title: Deciphering cell–cell communication during Arabidopsis seed development.
Project aims:This project aims to understand how cells communicate with each other to coordinate seed development by using scRNA-seq.
Certification of working with recombinant DNA
Professor Mathew Lewsey
AgriBio (L1Q4), ARC Research Hub for Medicinal Agriculture
La Trobe University
5 Ring Road, Bundoora VIC 3083, Australia
T: +61415921764
E: M.Lewsey@latrobe.edu.au
Certification of working with recombinant DNA