Visiting Scientist: AI-Driven Bibliometrics & Science

Hillspire; New York (NY); Presencial; USD 155.000 - 185.000; Tempo integral

Resumo da vaga

Schmidt Sciences invites applications for a 12-month Visiting Scientist position focused on bibliometrics and the science of science. The role blends measuring outcomes of programs with shaping scholarly infrastructure and the scientific record as AI reshapes research publication and verification.

Candidates should have a PhD, postdoc experience, and a track record in bibliometrics, with ability to work autonomously within interdisciplinary teams.

Qualificações

• A PhD or equivalent in information science, computer science, math, statistics, or related field.
• At least 2 years of postdoctoral or equivalent experience.
• Evidence of bibliometrics, scientometrics, or the science of science with peer‑reviewed work.
• Hands-on experience with large‑scale data on publications, citations, researchers, and collaboration networks.
• Demonstrated effective use of AI in research and data analysis.
• Experience building databases, analytical tools, or software for science of science.
• Ability to translate research into practical recommendations for program teams.
• Proven ability to operate autonomously within interdisciplinary teams.
• Be based on-site in New York and travel regularly within the U.S. and internationally.

Responsabilidades

• Portfolio Impact and Strategy: review program data collection, assess outcomes, and recommend improvements.
• Design and pilot approaches to tracking outcomes and interdisciplinary measures, using AI and large-scale bibliometric data.

Conhecimentos

Bibliometrics

Science of science

AI in research

Data analysis

Formação

PhD in information science/computer science/ math/ statistics

Ferramentas

Databases

Analytical tools

Descrição da vaga

Schmidt Sciences invites applications for a 12-month Visiting Scientist position focused on bibliometrics and the science of science. The role blends measuring outcomes of programs with shaping scholarly infrastructure and the scientific record as AI reshapes research publication and verification.

Candidates should have a PhD, postdoc experience, and a track record in bibliometrics, with ability to work autonomously within interdisciplinary teams.