Associate Research Scientist (PREP0004138) Full-time

Associate Research Scientist

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.

Research Title: Evaluation of search, natural language processing, multimedia, and generative information systems.

The work will entail: The National Institute of Standards and Technology's (NIST) Information Technology Laboratory is seeking a qualified candidate to support the Text Retrieval Conference (TREC, trec.nist.gov). TREC evaluates AI technologies in information retrieval (IR), search, natural language processing, and multimedia search, creating human-labeled data to measure effectiveness. TREC hosts annual evaluations & workshops, releasing datasets and research papers upon completion. The candidate for this position will work alongside world-class researchers at NIST.

U.S. Citizen Preferred

Key responsibilities will include but are not limited to: Develop software for topic creation, relevance assessment, and generative output annotation. Develop scoring software for evaluation outputs. Develop and maintain systems used to register, submit outputs, and see evaluation results. Conduct research on evaluating information access systems, including but are not limited to: Automating the evaluation of AI-generated outputs. Leveraging human insight and expertise with AI support for data annotation and evaluation. Designing metrics for AI-generated outputs in information-seeking contexts. Interfaces for annotating data that support consistency and identify errors. Quality control processes for data annotation. Leaderboard designs that support cooperative research instead of competition.

Qualifications: A PhD degree in Computer Science. 5+ years of relevant experience. Experience building systems with large language models as components. Familiarity with Docker and Git. Experience with Python, JavaScript, and web frameworks such as React and Django. Ability to develop prototypes of tools needed to analyze data. Strong oral and written communication skills.