Data Curation and Research Reproducibility Specialist

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How to Apply

A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.


In 2016 the University of Michigan Library embarked on an exciting initiative to address the research data management, sharing, and preservation needs of the University through providing a suite of data curation services. Data curation enhances the value of data sets through activities such as augmenting metadata, file format transformation, and digital preservation. The library’s data curators collaborate with researchers at all stages of the data lifecycle to provide support for sharing data in ways that are findable, accessible, interoperable and reusable (FAIR) as well as ethical. The Library operates its own data repository, Deep Blue Data, as a means of sharing and preserving research data developed at U-M.  

The Michigan Institute for Data Science (MIDAS) is the university-wide unit to support data science and Artificial Intelligence (AI). Central to MIDAS’ mission is to ensure U-M’s leading role in data science and AI research through enabling interdisciplinary research and transforming traditional disciplinary research with cutting-edge data science and AI methods, as well as training for investigators. In the past two years, MIDAS’ work to promote and to enable ethical and reproducible data science and AI research has been particularly well received by research communities from across the University, and has made MIDAS known among academic data science institutes for leading such work.  Reproducibility of research results is essential to any advancement in science. This and the ethical aspects of data science -- making data representative, unbiased and of high-quality -- is closely related and complementary to the Library’s data curation effort. The Library has also been a key collaborator in the research reproducibility activities organized by MIDAS.  

All of the efforts from the Library and MIDAS to improve the FAIRness of data, the quality and representativeness of data, the ethical use of data and the reproducibility of data science and AI research not only play an essential role to ensure U-M’s research leadership, but are also expected by scholarly societies and funding agencies. A major obstacle, however, is that at U-M (and at most other leading universities) there remains an urgent need to develop tools and resources that researchers have easy access to, and training that builds researchers’ skills to use such resources.  This new staff member will play a critical role in building systematic approaches for the massive adoption of best practices to ensure data FAIRness and the ethical and reproducible use of data. 

The Data Curation and Research Reproducibility Specialist is a joint position between the Library’s Deep Blue Repository and Research Data Services unit and MIDAS. This position is centered on understanding the needs of researchers in the reproducibility of their work and building resources, curating research data submitted to the Deep Blue Data repository with an emphasis on supporting reproducibility, and developing actionable standards and practical tools to improve the data quality with respect to representativeness and quality.

The Library is committed to recruiting and retaining a diverse workforce and encourages all employees to incorporate their diverse backgrounds, skills, and life experiences into their work. The Library’s Diversity Strategic Plan is at

NOTE: This is a 3-year term appointment.


In partnership with colleagues in the Library, MIDAS, as well as selected academic programs, institutes, departments, and colleges across campus, the person in this position will provide:

Development of Local Standards, Tools and Support

Using their knowledge of data and reproducibility best practices, as well as the needs of U-M researchers, the person in this position will design, develop and support local standards of practice for the Library, MIDAS and the U-M community to improve the FAIRness of data, data quality and representativeness, and the reproducibility of data-intensive research. These may include data collection and documentation standards, reproducible workflows, tools to support the rigor and transparency of research projects  This may include pursuing external funding depending on the expertise, interest and capacity of the person in this position.     

Data Curation and Reproducibility Evaluation

The person in this position will review data sets submitted to Deep Blue Data, in conjunction with other experts as needed, to assess the condition of the data set and to make recommendations to increase the FAIRness of the data set, address issues of bias, improve its quality, and ensure sufficient metadata  to permit the data to be reproduced or replicated. They will serve as a data curator in the Data Curation Network (, a consortium of academic libraries offering data curation and repository services. They will also serve as an independent reviewer for code, workflows or other components of research to help ensure their reproducibility. 


The person in this position will serve as a consultant for researchers on  best practices in data curation and reproducible research (such as developing reproducible research workflow, common tools for open science). Consultation activities will range from single meetings to address a particular need to longer-term collaborations with researchers to explore or address larger issues. This may include participating in funded research projects as a named collaborator.   

Education and Community Development

The person in this position will organize workshops and other educational programing on introductory and specialized topics to train researchers on improving data FAIRness and quality, the ethical and responsible use of data, and workflows and tools for reproducible research.    

Professional Development

Pursue enrichment and professional development activities as appropriate to the position and individual interests. Engage and contribute to the library, disciplinary, and other relevant communities of practice. 

Required Qualifications*

  • An advanced degree (Masters or PhD level) in a quantitative discipline, or a Master’s Degree in Library Science or equivalent combination of education and experience

  • Detailed knowledge of, or direct experience in, working with both structured and unstructured data in at least one main field of research, such as healthcare research, engineering research or social science research

  • Understands and values diversity and the importance of inclusion as demonstrated through a commitment to apply and incorporate the differences, complexities, and opportunities that diversity brings to an organization.

  • A strong understanding of research reproducibility and relevant tools, standards, and best practices

  • Demonstrated knowledge of, or direct experience in, managing, sharing, curating or preserving research data

  • Familiarity with the information technologies, standards, and best practices prevalent in working with data and how they could be applied

  • Experience in identifying the information needs of researchers and in developing effective responses or services to meet those needs

  • Excellent written and oral communication skills and a demonstrated ability to present and share ideas clearly and effectively to diverse audiences

Desired Qualifications*

  • Experience in working in an academic research environment or library

  • Direct experience with the information technologies, standards, or best practices prevalent in data curation and/or research reproducibility

  • Direct experience in conducting research and in managing, sharing or curating research data, and developing metadata

  • Experience working with data repositories

  • Experience in developing or supporting research based communities

Underfill Statement

This position may be underfilled at a lower classification depending on the qualifications of the selected candidate.

Additional Information

NOTE: Three year term appointment

Appointment is anticipated at the Assistant Librarian or Associate Librarian rank. The maximum salary for this position is $70,000.  The actual salary offered may vary based on the qualifications and experience of the selected candidate.

Physical Requirements/Work Environment

  • At this time, the Library is utilizing a hybrid work model (partially remote, partially in person), but a return to more in-person working is expected once public health guidelines permit. While access to a personal Internet connection is desirable, U-M Library provides support and resources for remote work needs.

  • The Data Curation and Research Reproducibility Specialist is a joint position between the Library’s Deep Blue Repository and Research Data Services unit and MIDAS. The person in this position will have office space available to them in the Library and MIDAS. 

Librarian appointments carry with them expectations regarding professional development, professional engagement, research, and service, in keeping with the library's process for librarian promotion and advancement.

The University of Michigan offers a comprehensive benefits package including generous time off (24 vacation days per year, and 15 sick leave a year), matched retirement contributions with immediate vesting, professional development opportunities and more.  TIAA and Fidelity Investments’ retirement options available.

Application Deadline

Job openings are posted for a minimum of seven calendar days.  This job may be removed from posting boards and filled anytime after the minimum posting period has ended.

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.

U-M COVID-19 Vaccination Policy

COVID-19 vaccinations, including boosters when eligible, are required for all University of Michigan students, faculty and staff across all campuses, including Michigan Medicine.  This includes those working remotely.   More information on this new policy is available on the Campus Blueprint website or the UM-Dearborn and UM-Flint websites.