I do not have prior experience in conventional data labeling tasks such as image annotation, text tagging, bounding-box
I do not have prior experience in conventional data labeling tasks such as image annotation, text tagging, bounding-box labeling, or large-scale manual labeling for general AI platforms. However, I do have strong AI training and scientific data preparation experience in biotechnology and computational biology. My work includes preparing, curating, analyzing, and validating complex biomedical datasets such as sequencing data, RNA-seq data, proteomics data, molecular simulation outputs, protein structure datasets, ligand libraries, and CRISPR guide RNA-related data. My AI-related experience is focused on applied scientific AI, including deep learning for mRNA and protein structure prediction, virtual ligand screening, CRISPR guide RNA selection, promoter site prediction, bioinformatics workflows, and AI-assisted drug discovery. Therefore, while I would not claim traditional data labeling experience, I can confidently claim experience in AI training support, scientific data curation, biological dataset interpretation, and domain-specific validation for biomedical AI projects.