Gabriel Dias Moreira

Key Skills

Software

OpenCV AI Kit (OAK)

Top Subject Matter

Data Annotation and Labeling for LLMs

Bioinformatics Data Processing and Model Optimization

Content Curation for Scientific and Technical Language Models

Top Data Types

Document

Image

Text

Top Task Types

Classification

Computer Programming Coding

Data Collection

Prompt Response Writing SFT

Text Generation

Freelancer Overview

As a biologist with a master’s in microbiology, I bring expertise in data annotation and processing for AI models, especially in life sciences. My background in microbiology, bioinformatics, and molecular biology enables me to curate and label high-quality datasets for training Large Language Models (LLMs) and other AI applications, ensuring scientific accuracy and relevance. I have hands-on experience in structuring datasets for genomic analysis, epidemiological surveillance, and public health data, skills that directly enhance AI applications for health and research. In addition to data labeling, I excel in developing and optimizing bioinformatics pipelines for genomic data processing, leveraging tools and statistical methods to refine AI outputs. My work with genomic sequences, pathogen surveillance, and data modeling provides a unique foundation for creating precise, specialized AI training data in the fields of genetics, microbiology, and health. These skills enable me to contribute to AI training projects that demand a deep understanding of scientific data and domain-specific languag

Labeling Experience

Genomic Annotation for Viral Surveillance AI Model

Opencv AI Kit OakTextEntity Ner ClassificationClassification

I contributed to a data labeling project focused on annotating viral genomic data for a machine learning model used in pathogen surveillance and outbreak detection. This project involved structuring and labeling large datasets of genomic sequences from Yellow Fever Virus (YFV) samples. My role required high precision in identifying genetic variants, assembling genomic data, and annotating key features to enhance model training and accuracy. Leveraging my background in microbiology and bioinformatics, I used specialized tools to preprocess and label data, ensuring the dataset's scientific accuracy and relevance to epidemiological applications. This experience has honed my ability to curate complex biological data for AI training, providing robust data inputs for health and public health AI solutions. This project reflects my proficiency in data annotation within genomics and public health, key areas in training AI to understand complex biological and health data.

I contributed to a data labeling project focused on annotating viral genomic data for a machine learning model used in pathogen surveillance and outbreak detection. This project involved structuring and labeling large datasets of genomic sequences from Yellow Fever Virus (YFV) samples. My role required high precision in identifying genetic variants, assembling genomic data, and annotating key features to enhance model training and accuracy. Leveraging my background in microbiology and bioinformatics, I used specialized tools to preprocess and label data, ensuring the dataset's scientific accuracy and relevance to epidemiological applications. This experience has honed my ability to curate complex biological data for AI training, providing robust data inputs for health and public health AI solutions. This project reflects my proficiency in data annotation within genomics and public health, key areas in training AI to understand complex biological and health data.

2023

Education

Work History