Research Assistant (Undergraduate)

Essential Duties

• We are seeking a motivated undergraduate student with Python experience to join Dr. Maya-Lastra’s research lab on a project in automated lexicon enrichment for botanical data. The successful candidate will help develop a bootstrap pipeline that expands an existing botanical lexicon by combining Dr. Maya-Lastra’s parser software, which integrates NLP and heuristic methods, with locally run large language models. The student will also lead an independent project enriching a second lexicon focused on a different plant group and comparing both lexicons to evaluate whether a single master lexicon or separate specialized lexicons better support botanical text processing.

Essential Duties

• Pipeline development: Build and maintain a bootstrap pipeline in Python that integrates the existing parser with locally run LLMs to identify and add new lemmas.
• Evaluation: Design and apply metrics to quantify lexicon improvement, such as coverage, precision of new entries, and parser performance before and after enrichment.
• Human verification: Coordinate the review of newly added lemmas, including preparing verification sets, tracking reviewer decisions, and incorporating corrections.
• Testing: Run and maintain tests to ensure the reliability and reproducibility of the pipeline.
• Independent project: Lead the enrichment of a second lexicon centered on a different plant group, and compare both lexicons to assess overlap, divergence, and performance.
• Documentation & Reporting: Document code, methods, and results, and prepare regular progress summaries for Dr. Maya-Lastra.

Benefits

• Gain hands-on research experience in applied NLP , LLM integration, and botanical data.
• Lead an independent research question from design to analysis.
• Opportunity to co-author reports, presentations, and publications.
• Possibility to present research at regional and national conferences.
• Mentorship and collaboration within an active research group.

Required Qualifications

• Enrollment in an undergraduate program
• Experience in Python
• Basic familiarity with handling text data and structured formats such as JSON or CSV
• Ability to work independently without supervision based on objectives

Preferred Qualifications

• Coursework or experience in natural language processing, computational linguistics, or botany.

Physical Demands

EEO Statement