Postdoctoral Associate in Meta-research - UEIS

Carnegie Mellon University • Pittsburgh, PA

3d • Onsite

About The Position

This is a fixed-term, 2-year position at Carnegie Mellon University Libraries, Evidence Synthesis specialists and the Open Science Program. The role focuses on investigating and promoting open science principles within evidence synthesis and meta-research methods, as well as computational approaches to improving research quality, transparency, reproducibility, and accessibility. The Postdoctoral Associate will develop a research and teaching agenda related to meta-research, evidence synthesis, and open science, utilizing open source tools. Meta-research is defined as the study of how research is conducted, communicated, evaluated, and synthesized to improve its quality, transparency, efficiency, and impact. The position involves collaborative research, teaching workshops, developing curriculum, serving on organizing committees for open science events, assisting with outreach efforts for the Evidence Synthesis Program, and contributing to international research communities. The role requires strong technical and computational skills, a solid understanding of the academic research ecosystem, and a passion for building an open and collaborative research community. Carnegie Mellon University offers a strong environment for meta-research with its Open Science program, Open Source Programs Office, leading Computer Science program, and faculty-librarian collaborations.

Requirements

• Ph.D. in a STEM or social science discipline.
• Strong interest in building an open science community across disciplinary boundaries and advancing the quality and rigor of research and open scholarship.
• Familiarity with or interest in learning about evidence synthesis and/or bibliometrics methods.
• Experience with coding and programming in R or Python. Should be proficient enough to work independently with standard packages and troubleshoot basic issues.
• Enthusiasm for working collaboratively with library personnel on research projects, instructional design, and developing services.
• Strong track record in academic research in a discipline that is well established at CMU (relevant research experience in industry or government also considered).
• Demonstrated record of teaching excellence in academic settings including hands-on training or training others in computational skills. Interest in refining teaching skills and curriculum development.
• Experience conducting research on at least one of the following areas: evidence synthesis methods, meta-research, bibliometrics, reproducibility, open science, or scholarly communication.
• Knowledge of conduct and reporting standards for evidence synthesis (e.g., PRISMA).
• Understanding of computational reproducibility best practices.
• Familiarity with machine learning concepts and large language models. Deep expertise is not required, but candidates should be comfortable engaging with these technologies at a foundational level.
• Knowledge of tools used for reproducible research such as Git/GitHub, Jupyter Notebook, Binder, Docker, Open Science Framework.
• Strong interpersonal skills with the ability to effectively interact with diverse groups including faculty, students, staff, and administrators.
• Demonstrated ability to work independently and as part of a team.
• Excellent organizational, communication, and presentation skills.
• Dedication to professional development including personal research and scholarship and growth of skills.
• Interest in contributing to the global open science community.
• Applicants for this position must be currently legally authorized to work for CMU in the United States. CMU will not sponsor or take over the sponsorship of an employment visa for this opportunity. Carnegie Mellon is not a qualifying employer for the STEM OPT benefit: only the 12-month OPT may be used to work at Carnegie Mellon.

Responsibilities

• Conduct collaborative research in meta-research, including topics such as transparency and reproducibility in evidence synthesis; computational methods for literature discovery, study selection, and data extraction; evaluation of AI and open source tools that support meta-research workflows; living evidence synthesis methods; and/or bibliographic infrastructure.
• Teach workshops and develop curriculum on topics such as using large language models for evidence synthesis, using open source software to manage and conduct literature review, and/or the ethical and appropriate use of scholarly information in meta-research.
• Serve on organizing and programming committees of open science and evidence synthesis events hosted by the Libraries, including the annual Open Science Symposium and an inaugural meta-research hackathon to be held in Spring 2027.
• Assist in the outreach efforts of the Libraries' Evidence Synthesis Program including the support of research tools such as Sysrev and OpenAlex.
• Contribute to international research communities, such as Metascience, FORCE11, or ESMARConf, with poster presentations or talks on open synthesis and meta-research.

Benefits

• Comprehensive medical, prescription, dental, and vision insurance
• Generous retirement savings program with employer contributions
• Tuition benefits
• Ample paid time off
• Observed holidays
• Life and accidental death and disability insurance
• Free Pittsburgh Regional Transit bus pass
• Access to Family Concierge Team
• Fitness center access

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree