AI Applications in Butterfly Taxonomy and Biodiversity Internship

About Internship

Former Professor in Zoology from Chandigarh University, India, is accepting interns interested in the field of Biology, in the research area of Biodiversity & Taxonomy.

This internship is designed to explore the innovative application of Artificial Intelligence (AI) prompt engineering in biodiversity documentation and taxonomic research, with a focused case study on butterflies. The program integrates classical taxonomic methodologies with modern AI-assisted tools to enhance research efficiency, data synthesis, and scholarly output while maintaining scientific rigor and ethical standards. During the internship, students will: 1. Apply AI-based prompt engineering techniques to support biodiversity and taxonomic research workflows. 2. Curate, organize, and analyze morphological, ecological, and molecular data related to butterfly species using publicly available biological databases. 3. Integrate AI-generated insights with classical taxonomic literature for species identification and comparative analysis. 4. Design and test domain-specific prompts for AI tools (such as ChatGPT) tailored to biodiversity and taxonomy research needs. 5. Assist in bioinformatics-supported workflows and evaluate the reliability and authenticity of AI-assisted outputs. 6. Contribute to structured research documentation, annotations, and short scholarly manuscripts under academic supervision. Research Focus: The internship proposes a systematic evaluation of AI prompt-based systems as supportive tools in butterfly biodiversity and taxonomic research. Emphasis will be placed on assessing the effectiveness of AI in organizing taxonomic literature, correlating morphological and molecular datasets, and enhancing research productivity while ensuring responsible and ethical use of artificial intelligence in biological sciences. Mode of Internship and Expected Outcomes: The internship will be conducted entirely in virtual mode, with periodic academic interactions, mentoring, and review meetings organised as required through Zoom or Google Meet. The primary objective of the programme is capacity building in AI-assisted biodiversity research, with a specific focus on the preparation of concise, high-quality research papers intended for publication in ISBN-based edited volumes or similar academic compilations.