Research Assistant - AI model training and data curation
Contributed to the application of Python-based deep-learning models for pattern detection in scientific experimental data. Supported biological data analysis and statistical assessment using R and other bioinformatics tools to interpret genetic data. Assisted in managing and curating experimental datasets to improve clarity and reliability for research outputs. • Utilized deep learning models to identify relevant biological patterns from text-based research data. • Performed data preprocessing and curation, ensuring datasets met quality criteria for model training. • Engaged in preparing training datasets for AI models by validating and tagging experimental outcomes. • Helped integrate labeled information into structured SQL databases for streamlined retrieval and analysis.