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A bit about me...

I am Aviad, a computational biologist passionate about genomics and biomedical science. Over the past 8+ years, I have gained extensive practical expertise by immersing myself in genome centers and bioinformatics labs. 
My work has involved diverse projects and organisms, ranging from population genomics and medical-oriented genomics to Transposable elements and codon-usage bias analysis. 

I have worked with data from mammals, yeast, plants, and viruses, which has allowed me to develop a comprehensive understanding of genomics across different biological systems.

Staying up-to-date with the latest advancements in the field is a crucial aspect of my work. This is reflected in my proficiency with multiple coding languages and my use of cutting-edge tools and techniques.

By leveraging these resources, I aim to deliver the highest quality analysis and contribute to the ever-evolving field of genomics.

Relevant Experience

Technion Genome Center,

At the Technion Institution Genome Center, I gained valuable experience working on various projects, including complex time-series RNAseq analysis, single-cell RNAseq, Virus Assembly, and variant calling.

In addition, I played a crucial role in organizing scripts and updating the entire pipeline of different analyses. 

My work experience at the Technion Institution Genome Center also allowed me to effectively interact with clients and manage project results.

Bar-Ilan University - Faculty of Medicine Genome Center,

I worked as a bioinformatician, where I had the opportunity to establish pipelines for various types of analyses. This included RNAseq, Transposable-elements abundance analysis, Enrichment analysis, and working with data from cell-free RNA sequencing.

Additionally, I added verification and quality control steps to the analysis process as part of my role. This involved detecting ribosomal RNA, assessing library complexity, and identifying possible contaminations in the sequencing results. By implementing these measures, I ensured the accuracy and reliability of the analysis outcomes.

MIGAL Research Center, the Population Genomics Lab,

I worked as a bioinformatics scientist, focusing on unraveling the mysteries of population structure, mutation rates, and genetic signatures across various plant genomes. One notable project I was involved in was a field experiment that studied hundreds of wild barley lines. This research aimed to investigate domestication patterns in regional populations and involved conducting Genome-Wide Association Studies (GWAS) analysis. Through this experience, I honed my skills in data analysis and interpretation.

Master's degree, Cancer Genomics Lab at the Azriely Faculty of Medicine,

I established a dual system to predict protein expression levels during the cell cycle. This involved analyzing codon usage bias and its correlation with protein expression. I created a computational model leveraging an algorithm trained on human proteomic data to predict protein expression levels accurately. I developed a cell culture separation system using Flow Cytometry and various cell cycle markers to validate and refine the predictions. This multidisciplinary approach allowed me to understand better cancer genomics and the intricate relationship between protein expression and cell-cycle dynamics.

Technical Skills:

Coding languages - R, Python, Perl, SQL.

Unix/Linux systems administration.

NGS bioinformatics toolsets via command line.

Pipeline implementation and maintenance.

Bioinformatics Skills:

RNAseq analysis, miRNAseq analysis, scRNAseq analysis, variant calling, genome assembly, methylation sequencing analysis, and population genomics.


Population genomics, Hubner lab.

Population Codon-usage, Morgenstern lab.


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