Graduate Assistant Position, Grant-Funded NLP/Text Mining Research Project
Dr. LaTesha Velez is seeking one graduate assistant for a paid grant-funded position supporting an IMLS-funded research project. This position is specifically focused on text mining, natural language processing (NLP), and sentiment analysis using large language models (LLMs).
Grant summary:
In this Early Career Research Development project, Dr. LaTesha Velez at the University of North Carolina at Greensboro is leading a team investigating how Latine people are depicted in English-language library and information science (LIS) research publications. The project examines questions such as: What conversations does the LIS profession have about Hispanic/Latine people? What patterns appear in LIS research about Latine communities? What biases, assumptions, or recurring narratives appear in this scholarship?
The next phase of the project will use text mining, NLP, and sentiment analysis with LLMs to analyze full-text LIS research articles. The goal is to better understand patterns in language, representation, framing, and sentiment across the project corpus.
Primary role and responsibilities:
This graduate assistant’s primary responsibility will be to move forward the project’s text mining and NLP work. Responsibilities may include:
Working 20 hours per week from May 2026 through the end of the grant, likely July 2027
Preparing full-text article files for computational analysis
Cleaning, structuring, and organizing text data
Developing and testing text mining workflows
Supporting NLP analysis of the project corpus
Conducting sentiment analysis, including analysis using LLMs
Helping develop prompts, procedures, and documentation for LLM-assisted analysis
Identifying patterns in language, framing, sentiment, and representation
Creating tables, summaries, and visualizations based on text mining and NLP outputs
Documenting methods clearly so the work can be explained, evaluated, and replicated
Meeting regularly with the project team to discuss findings, troubleshoot methods, and refine analysis
Contributing to conference presentations, manuscripts, and project deliverables, when appropriate
Required qualifications:
Applicants should have experience with, coursework in, or a strong demonstrated interest in text mining, NLP, computational text analysis, sentiment analysis, or LLM-assisted research.
Applicants should also have:
Strong attention to detail
Ability to work independently and troubleshoot technical problems
Ability to work with large amounts of text data
Strong organizational and documentation skills
Interest in applying computational methods to equity-focused research
Ability to communicate technical processes clearly to a research team
Ability to attend regular virtual meetings and provide progress updates
Preferred qualifications:
Experience with Python, R, or another programming language used for text analysis
Experience with NLP tools, packages, or libraries
Experience with sentiment analysis
Experience using LLMs for research, coding, classification, or text analysis
Experience with prompt development, prompt testing, or evaluating LLM outputs
Experience with topic modeling, keyword extraction, named entity recognition, classification, clustering, or related methods
Experience cleaning and preparing full-text documents for analysis
Experience creating reproducible workflows or clear methodological documentation
Familiarity with LIS research, Latine studies, critical race theory, discourse analysis, or equity-focused scholarship
Applicants do not need to have experience in all preferred areas. The strongest candidates will be able to demonstrate technical skill, curiosity, and the ability to help the team thoughtfully apply computational methods to questions of representation, equity, and language.
Salary:
This is a paid grant-funded graduate assistant position. The hourly rate is expected to be approximately $25/hour, but the final rate and appointment details will be determined by UNCG policies and grant administration.
Why apply to work on this grant?
This position offers an opportunity to gain hands-on experience with grant-funded research, text mining, NLP, LLM-assisted sentiment analysis, and equity-focused LIS scholarship. Benefits may include:
Ability to work remotely
Experience with computational text analysis in an active research project
Opportunity to help shape the project’s NLP and LLM-assisted sentiment analysis workflows
Opportunity to be listed as a co-author on articles, depending on level of contribution
Opportunity to contribute to conference presentations
Grant funding to support conference presentations
Professional research mentorship
Position dates:
The position will begin in May 2026 and continue through the end of the grant, likely July 2027.
To apply:
Please email your CV or resume and cover letter to Dr. LaTesha Velez at lmvelez@uncg.edu. Virtual interviews will be scheduled with selected candidates. The position will remain open until filled.
In your cover letter, please describe your experience or interest in text mining, natural language processing, sentiment analysis, large language models, computational text analysis, or related methods.
If you have questions, please contact Dr. Velez at lmvelez@uncg.edu.
