Assistant Research Scientist

PREP Research Associate 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 Reliability of Human and LLM Annotations for AI Risk Assessment The work will entail This project focuses on using Large Language Models (LLMs) to provide annotations of evaluation data (a.k.a., LLM as judge), and the design of an Inter‑Annotator Agreement study to assess the reliability of both human and LLM annotations. The candidate will explore assessing the indicators of a given AI‑related risk, determining how to identify them, and providing annotators with examples to annotate the presence of various risks. The project aims to develop an annotation framework for AI risk assessment and establish metrics for data quality in AI risk research, supporting broader work at NIST in assessing and measuring the validity and reliability of AI‑related risks in data annotation. U.S. Citizen Preferred Key Responsibilities Gain familiarity with existing literature on data annotation and LLM as judge Understand NIST's role and ongoing efforts in assessing and measuring the validity and reliability of AI‑related risks in data annotation Contribute to developing an annotation framework for AI risk assessment Collaborate effectively with cross‑functional and interdisciplinary stakeholders to ensure successful project outcomes Deliverables Contributions to a NIST report that supports ongoing NIST AI evaluation efforts focused on the design of an Inter‑Annotator Agreement to assess the reliability of both human and LLM annotations. Qualifications Background in Computer Science, Data Science, or related field. Education level: Bachelor\'s or Graduate Degree Strong interest in data annotation and AI risks Familiarity with scientific reading and technical writing Salary Range The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. 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. Total Rewards Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: 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. Vaccine Requirements Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. The COVID-19 vaccine does not apply to positions located in the State of Florida. 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The pre‑employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre‑employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office. 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 OHB System AG