Key Skills

Freelancer Overview

As a Molecular Biology PhD candidate at UCLA with a background in virology, immunology, and vaccine development from my undergraduate research at Cornell University, I am new to AI training and data labeling. However, my strong foundation in scientific research, including hands-on laboratory work in host-pathogen interactions, molecular pathogenesis, and antiviral synthesis, positions me to contribute effectively to AI projects in biological and medical domains. My analytical skills in experimental design, data interpretation, and molecular techniques—such as primer design, mammalian cell culture, and molecular cloning—enable me to evaluate and annotate complex scientific data with precision and attention to detail. I believe I can best contribute to AI training in areas like biomedical data labeling, where my expertise in virology (e.g., coronavirus and paramyxovirus mechanisms) and immunology can help assess model outputs for accuracy in health-related simulations, drug discovery, or pathogen modeling. Additionally, my teaching experience as a general chemistry tutor and course assistant at Cornell has honed my ability to break down complex concepts, making me adept at creating high-quality annotations for educational or scientific AI datasets.

Labeling Experience

Education

Work History