Assistant Research Scientist (PREP0003673)

Project Overview This project focuses on documenting the Assessing Risks and Impacts of AI (ARIA) dataset, which is used to evaluate risks as part of a NIST ARIA Program. The student will assist in the design and development of a comprehensive dataset card aligned with emerging standards for AI, including the principles of transparency, reliability, and reproducibility. This work supports the advancement of rigorous, standardized data documentation practices consistent with federal and international frameworks. Key Responsibilities Collaborate with AI researchers to develop a dataset card documenting the technical and operational parameters of datasets used in AI evaluations and emerging AI standards. Identify and describe the dataset's technical parameters, including intended use, limitations, collection methods, and risk‑relevant features. Conduct quality assurance checks to detect anomalies, inconsistencies, and completeness issues in the dataset. Assist in the preparation of the dataset for public release, including metadata curation, file organization, and access provisioning. Apply and assess data anonymization techniques to ensure privacy compliance and mitigate re‑identification risks. Deliverables A dataset card following relevant documentation standards. A finalized version of the dataset curated for public release, with accompanying metadata. A report summarizing identified data limitations, anonymization procedures applied, and mitigation strategies for potential risks. A checklist‑based audit log of quality assurance checks performed. Qualifications Background in Data Science, Computer Science, Information Science, HCI, or a related field. Education level: graduate student. Familiarity with dataset documentation standards and risk assessment frameworks (e.g., NIST AI Risk Management Framework). Strong written communication skills for technical documentation. Compensation and Benefits Salary Range: The referenced salary range represents the minimum and maximum salaries for this position. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University. Equal Opportunity Employer The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved. Background Checks The successful candidate(s) for this position will be subject to a pre‑employment background check including education verification. EEO Is The Law #J-18808-Ljbffr Inside Higher Ed