Key Skills

Freelancer Overview

Biotechnology specialist with advanced expertise in preparing, annotating, and validating biological datasets for AI-driven research and predictive modeling. Proficient in structuring high-dimensional genomic, proteomic, and clinical data to train machine learning algorithms, utilizing tools like R, Python, Galaxy, and Cytoscape. Skilled in data preprocessing, metadata tagging, and quality control for NGS, RNA-seq, and molecular interaction networks, ensuring datasets meet AI/ML readiness standards. At Baheya Research Center, contributed to genetics studies by annotating genomic variants and curating breast cancer biomarkers, refining datasets for oncology-focused AI applications. Led a graduation project analyzing estrogen-Lactobacillus interplay in metastasis, requiring precise annotation of hormonal-microbiome datasets to identify patterns for predictive model development. Certified in Data Analysis & Visualization (DAV-R) via EgCompBio, with hands-on experience designing training modules to upskill teams in AI-relevant bioinformatics workflows, including data cleaning, feature extraction, and reproducible analysis pipelines. Combined expertise in CRISPR, qPCR, and clinical pathology enhances ability to contextualize biological data for AI training, while Total Quality Management (TQM) training ensures adherence to compliance in large-scale data annotation. Adept at bridging wet-lab insights with computational rigor to optimize AI model accuracy in healthcare innovation.

Labeling Experience

Education

Work History