Are you a recent Ph.D. graduate in a STEM or social science
discipline interested in a career path in meta-research, knowledge
synthesis, open science and/or improving the quality and rigor of
research? Join the team of Evidence Synthesis specialists and the
Open Science Program at Carnegie Mellon University Libraries, where
we are working to investigate and promote open science principles
within evidence synthesis and meta-research methods as well as
computational approaches to improving the efficiency, transparency,
reproducibility, and accessibility of research across
disciplines.
The Postdoctoral Associate in Meta-Research should be technically
and computationally skilled, have a strong understanding of
academic research and the research ecosystem and be passionate
about building an open and collaborative research community. The
successful candidate will develop a research and teaching agenda
related to meta-research, evidence synthesis, open science, and
research improvement using open source tools and technologies. This
is a fixed term 2-year position with 50% of time devoted to
research and 50% to teaching and community-building
activities.
Meta-research is the study of how research is conducted,
communicated, evaluated, and synthesized, with the goal of
improving the quality, transparency, efficiency, and impact of
research. One emerging area within meta-research is
open
synthesis, which combines open science principles with evidence
synthesis methods such as systematic reviews, scoping reviews, and
evidence and gap maps. With the exponential growth of scholarly
publishing, increasing demand for evidence-informed decision
making, and rapid advances in artificial intelligence and large
language models, there is a growing need to investigate questions
at the intersection of meta-research, open science, and evidence
synthesis. This includes research and capacity-building efforts
related to:
- Improving the openness, accessibility, and interoperability of
scholarly information and bibliographic metadata;
Developing and evaluating open source software, AI tools, and
computational workflows that support evidence synthesis and other
forms of meta-research;
Advancing transparency, reproducibility, and reporting
standards for research and evidence synthesis;
Developing living evidence syntheses and workflows for keeping
research knowledge current using open bibliographic data and
automated methods.
Carnegie Mellon University is well-poised to advance meta-research
with one of the first library-based
Open Science programs , an
Open
Source Programs Office , one of the leading
Computer Science
programs in the world, and a unique
Evidence Synthesis Program with deep
faculty-librarian collaborations across the university. The
Postdoctoral Associate in Meta-Research will work across these
departments and units to develop a variety of research and training
initiatives.
Core responsibilities will include:
Under the supervision of the Director of the Evidence Synthesis
Program, the successful candidate will:
- 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.
Adaptability, excellence, and passion are vital qualities within
the UEIS. We are in search of a team member who can effectively
interact with a varied population of internal and external partners
at a high level of integrity. We are looking for someone who shares
our values and who will support the mission of the university
through their work.
You should demonstrate:
- 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.
Qualifications:
- 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.
To Apply
A successful candidate would preferably be in place as early as
possible. To be considered, please include your CV, a cover letter,
and contact information for three references in your
application.
We strongly encourage applications from members of groups that have
been marginalized and/or underrepresented in academic librarianship
and who will contribute to the breadth of our organization.
Deadline: Applications received by August 15 will be given first
consideration.
Additional Information:
Sponsorship : 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.
Fixed Term: This is a fixed-term position with an
estimated duration of two years.
Joining the CMU team opens the door to an array of exceptional
benefits.
Benefits eligible employees enjoy a wide array of
benefits including comprehensive medical, prescription, dental, and
vision insurance as well as a generous retirement savings program with employer
contributions. Unlock your potential with tuition benefits , take well-deserved breaks with
ample paid time off and observed holidays , and rest easy with life and accidental
death and disability insurance.
Additional perks include a free Pittsburgh Regional Transit bus
pass, access to our Family Concierge Team to help navigate
childcare needs, fitness center access , and much more!
For a comprehensive overview of the benefits available, explore
our Benefits page .
At Carnegie Mellon, we value the whole package when extending
offers of employment. Beyond credentials, we evaluate the role and
responsibilities, your valuable work experience, and the knowledge
gained through education and training. We appreciate your unique
skills and the perspective you bring. Your journey with us is about
more than just a job; it’s about finding the perfect fit for your
professional growth and personal aspirations.
Are you interested in an exciting opportunity with an
exceptional organization?! Apply today!
Location
Pittsburgh, PA
Job Function
Pre/Post-Doctoral Associates & Fellows
Position Type
Postdoctoral Associate / Fellow (Fixed Term)
Full Time/Part time
Full time
Pay Basis
Salary
More Information:
- Please visit “ Why Carnegie Mellon ” to learn more about
becoming part of an institution inspiring innovations that change
the world.
- Click here to view a listing of employee benefits
- Carnegie Mellon University is an Equal Opportunity
Employer/Disability/Veteran .
- Statement of Assurance
