Research Assistant: Automated Publication Pipeline & Tools

Penn State University; University Park (TX); In loco; USD 19.000 - 25.000; Part-time

Descrizione del lavoro

Penn State University Park invites applications for a part-time research assistant to support a team led by Professor Aydin Alptekinoglu. The role involves building an automated data pipeline for Smeal faculty papers and developing search tools, with up to 15 hours per week during the academic semester.

The position emphasizes Python scripting, API usage, data cleaning, and experience with LLM APIs. Remote work is not guaranteed and a background check may be required.

Competenze

• Currently enrolled Penn State student
• Strong Python skills with maintainable scripts and APIs
• Experience collecting and cleaning data programmatically (scraping, Crossref, Semantic Scholar, SSRN, PDFs)
• Familiar with large language model APIs (OpenAI, Anthropic, or similar) and prompt design
• Basic understanding of embeddings, vector search, and retrieval-augmented generation (RAG)
• Comfort with Git and basic software testing practices
• Ability to work independently and document code clearly

Mansioni

• Build and maintain an automated pipeline that collects Smeal faculty publications and working papers
• Develop and test search and discovery tools over the repository
• Support development of synthesis and translation features for faculty, research centers, marketing, and development
• Test the system with a small pilot collection, then scale to the full collection

Conoscenze

Python

APIs

Data collection

LLM APIs

Embeddings

Git

Documentation

Independent work

Strumenti

Streamlit

Flask

Descrizione del lavoro

Penn State University Park invites applications for a part-time research assistant to support a team led by Professor Aydin Alptekinoglu. The role involves building an automated data pipeline for Smeal faculty papers and developing search tools, with up to 15 hours per week during the academic semester.

The position emphasizes Python scripting, API usage, data cleaning, and experience with LLM APIs. Remote work is not guaranteed and a background check may be required.