Postdoctoral Associate in Evidence Synthesis - UEIS - University Libraries

Are you a recent Ph.D. graduate in a STEM or social science discipline interested in a career path in knowledge synthesis, open science, and/or meta-research? Join the team of Evidence Synthesis specialists and the Open Science & Data Collaborations program at Carnegie Mellon University Libraries, where we are working to investigate and promote open science principles and methods towards a more efficient, effective and accessible synthesis of research knowledge across disciplines.

The Postdoctoral Associate in Evidence Synthesis should be technically and computationally skilled, have a strong understanding of academic research and the research ecosystem, be passionate about building an open and collaborative research community, and committed to developing a research and teaching agenda on topics related to evidence synthesis 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.

Open Synthesis is a recently coined term that brings together open science principles and practices with evidence synthesis methods, such as systematic review and evidence and gap maps. With the exponential increase in academic publishing, the desire for evidence-based policy and decision-making, and recent advancements in AI and large language models, there is a need to investigate opportunities at the intersection of open science and evidence synthesis. This includes research and capacity-building efforts related to:

• Addressing challenges in the openness of bibliographic metadata and scholarly information

• Open source software and platforms for evidence synthesis, including development, testing and training on new and emerging technologies

• Guidance and best practices for transparency and reproducibility in reporting evidence synthesis methods and sharing research outputs

• The development of living evidence summaries and reviews that make use of new open bibliographic datasets and open source automation techniques, with an eye toward accessibility and usability

Carnegie Mellon University is well-poised to make significant contributions to this field 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 Evidence Synthesis will work across these departments and units to develop a variety of research and training initiatives.

Under the supervision of the Director, Evidence Synthesis Program, the successful candidate will:

• Conduct collaborative research on topics of open synthesis such as research transparency and reproducibility in evidence synthesis, living systematic review methods, computational approaches to finding and selecting studies for reviews, or the implications of open access policies and practices on evidence synthesis methods;

• Teach workshops and develop curriculum on open synthesis topics such as using large language models for evidence synthesis or using open source software to manage and conduct literature review;

• Serve on organizing and programming committees of open science events hosted by the Libraries, including the annual Open Science Symposium;

• Assist in the outreach efforts of the Libraries' Evidence Synthesis and Open Science programs including the support of research tools such as Open Science Framework, R, Python, and GitHub;

• Contribute to international research communities, such as Metascience or ESMARConf, with poster presentations or talks on open synthesis.

What We Require

• Ph.D. in a STEM or social science discipline;

• Strong interest in building an open science community across disciplinary boundaries and advancing open scholarship and reproducible research;

• Familiarity with evidence synthesis methods such as systematic reviews, living reviews, scoping reviews, or systematic maps.

• 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.

What We Would Like You To Have

• 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 evidence synthesis in any discipline and an understanding of current best practices, and knowledge of conduct and reporting standards for evidence synthesis;

• 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.

What We Can offer

• Professional development and travel funds are available.

• Hybrid work modality with 1-2 days per week from home.

• 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

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. This position requires a background check.

Flexibility, excellence, and passion are vital qualities within the CMU Libraries. Inclusion, collaboration, and cultural sensitivity are valued competencies at CMU. Therefore, we are searching for a team member who can effectively interact with a diverse 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.

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 February 28 will be given first consideration.

Additional Information:

• Sponsorship: Applicantsfor this positionmust becurrentlylegally authorized to workfor CMUin the United States. CMU will notsponsor or take over 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.

Joining the CMU team opens the door to an array of exceptional benefits available to eligible employees.

Those employees who are benefits eligible have the opportunity to experience the full spectrum of advantages from comprehensive medical, prescription, dental, and vision insurance to an enticing retirement savings program offering a generous employer contribution. You can also unlock your potential with tuition benefits and take well-deserved breaks with ample paid time off and observed holidays. Finally, rest easy knowing you are covered by life and accidental death and disability insurance.

Other perks include a free Pittsburgh Regional Transit bus pass, our Family Concierge Team to help navigate childcare needs, fitness center access, and so much more!

For a comprehensive overview of the benefits that may beawaiting you, explore our Benefits page.

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond just credentials, we consider the role and responsibilities, your invaluable work experience, and the knowledge gained through education and training. We acknowledge and appreciate your unique skills and the diverse 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!

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