Postdoctoral Research Associate in Data Science and Race, Place, and Equity

The School of Data Science at the University of Virginia invites applications for a full-time, postdoctoral research associate position, beginning August 2023 or earlier. The associate will be among 30 funded by an ambitious, University-wide Mellon Foundation Grant on Race, Place, and Equity focused on developing an undergraduate curriculum and advancing graduate and faculty research on the natural and cultural landscapes that encode local and national histories. The grant builds on the University’s strengths in teaching about racial equity and democracy as well as on the acute need for reckoning about race and place in Charlottesville, Albemarle County, and the University. The position is appointed for two years, contingent on a successful annual review. 

The School of Data Science at the University of Virginia was established in 2019 with the largest private gift in its two century history. The School seeks to set the standard in improving human and social conditions through the use of data, broadly conceived, from their collection and use to the development of novel methods and impactful applications. A core strategy in pursuit of this mission is to be a “school without walls,” connecting a diverse range of disciplines and professions through the common language of data. The primary vehicle for these connections is the collaboratory — an organization that connects faculty, staff, students, funding, infrastructure, and other resources with the goal of joining the science of data to teaching and research in specific domains.  

Candidates must have completed a PhD, preferably in an arts or humanities field, prior to the appointment start date. In the context of this initiative, the School seeks candidates who have expertise in digital humanities or an ethics-related field with an emphasis on racial equity. For each area, the School intends to  establish a center or collaboratory with which the associate will be affiliated, participating in activities and leveraging resources to pursue the objectives of the position. Within these roles, candidates may have expertise in analyzing or visualizing spatial or archival data sets, including maps, archaeological remains, legal records, oral histories, demographic data, and other sources that inform the connection between race as experienced and race as constructed. Regarding available data, there are opportunities to work with datasets that have been collected by other local projects, including the former Virginia Center for Digital History, which built an archive of photos, letters, and regional censuses relating to racial segregation laws and focused on Charlottesville. Methodologies that integrate macro levels of statistical description with local and situated descriptions are of particular interest. An area specialization in North America is preferred. Broadly speaking, the candidate must demonstrate potential for effective research in areas at the intersection of race, geography, history, and data. 

Among the direct benefits for associates are access to faculty mentoring, participation in a unique cohort in a vibrant initiative, and professional development. More broadly, associates may participate in UVA’s diverse system of organizations related to digital humanities and ethics, including the Institute for Advanced Technology in the Humanities, the Scholars’ Lab, the Digital Humanities Certificate Program, and the Institute of the Humanities and Global Studies.

To Apply: 

Please visit the UVA job board https://uva.wd1.myworkdayjobs.com/UVAJobs   and search for #R0043766. 

Complete the application online and attach the following:​

• A cover letter stating your interest in taking the position.
• A one page statement describing your research experience and the specific research areas that you would like to explore as part of the postdoc program. Additionally, you may identify 2 or 3 faculty mentors at UVA with whom you’d like to collaborate.
• A curriculum vita.
• The name, title, and email address of three faculty referees who have a strong sense of your goals and capabilities and who have agreed to write on your behalf.

***Please note that you MUST upload ALL documents into the CV/Resume box.

Applications that do not contain all of the required documents will not receive full consideration.***

For questions about the positions, please contact Raf Alvarado ([email protected]).

For questions about the application process, please contact Rhiannon O’Coin ([email protected]).

For more information about the Mellon Grant, please see news.virginia.edu/content/5-million-mellon-grant-backs-new-academic-program-race-place-and-equity  

For more information about the School of Data Science, please see datascience.virginia.edu . 

For more information about the University of Virginia and the Charlottesville community, please see www.virginia.edu/life/charlottesville and embarkcva.com .

For more information about benefits available to postdoctoral associates at UVA, visit postdoc.virginia.edu and hr.virginia.edu/benefits .

The selected candidate will be required to complete a background check at the time of the offer per University Policy.

COVID Vaccination Requirement and Guidelines

Please visit the UVA COVID-19 Job Requirements and Guidelines  webpage prior to applying for current information regarding vaccination requirements and guidelines for employment at UVA.

The University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff.  We believe diversity is excellence expressing itself through every person’s perspectives and lived experiences.  We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.