Post-Doctoral Research Associate : School of Data Science and School of Education and Human Dev...

Job description

Job location: Charlottesville, VA


Employment Type: Full-time
Posted data: 2020-10-22
Req: R0019512

The University of Virginia School of Data Science is seeking a Post-Doctoral Research Associate to be a part of a collaboration with the School of Education and Human Development focused on best practices for including equity, bias and fairness assessments of ongoing machine learning focused educational research. The candidate will be embedded into the newly formed “Collaboratory” between the two schools. Details of the goals of the collaboratory and expectations for the role are below.

Educational Data Science Collaboratory: Dr. Brian Wright, Dr. Vivian Wong and Dr. Benjamin Castleman have launched a joint venture that sits at the intersection of data science and education research. The goal of this “collaboratory” is to create a mutually beneficial and sustainable relationship that supports the broad mission of UVA and the discrete goals of the School of Education and Human Development and the School of Data Science while working to expand the knowledge and practice of the field of data science into the field of education. The Collaboratory’s work centers on two main projects, 1) develop an open-source recommendation engine that state agencies, higher education institutions, and workforce development organizations can use to provide their constituents with personalized employment guidance and 2) crowdsourcing research efforts that provide an alternative approach to the traditional paradigm of single, independent investigators conducting research. Crowdsourced research harnesses the power of the larger scientific community and shared online resources (Makel et al., 2019; Uhlmann et al., 2018) to accelerate the accumulation of knowledge. Projects have also begun that focus on developing a Data Schema for education research using Natural Language Approaches and building a classifier system that can assess whether education technology platforms are viable options depending on school demographic and survey data.

Foundational to these efforts are embedded practices to identify and eliminate machine learning bias that might be present and negatively affect the ability to move these projects forward. In doing so, the collaboratory and the School of Data Science has committed funds to support a fulltime post-doctoral research associate that will focus on developing and using current best practices for identifying systemic bias and fairness issues associated with generating machine learning research, specific to the field of educational and the projects as described above. The goal is to create an environment where methods centered on machine learning fairness can be developed in collaboration with domain experts and then shared broadly to encourage best practices and increase awareness.

Given the scope of these ongoing projects and the needs associated with each it is anticipated that this role will not be limited to developing and applying fairness measures but also contribute systemically to the development of the analytical methods necessary to make these projects successful. It is the view of the contributing researchers that this is a critical step to ensure complete knowledge of the goals, data and methods being used which will allow for more effective application of bias or fairness assessments. It should be noted that the School of Data Science also includes a Center for Ethics and Justice that will be a key contributor to this effort. Moreover, the School recognized that methods for assessing fairness or bias of machine learning algorithms is a new and growing field. Consequently, applicants that are interested in the intersection of Education and Data Science domains broadly are encouraged to apply.

Interested candidates must have earned or be on track to earn a terminal degree by the start date of the position.

This is a one year appointment with the possibility of renewal for up to three years. The anticipated start date is January 2021, later start dates may be considered.

TO APPLY:

PROCESS FOR INTERNAL UVA APPLICANTS: Please apply through your Workday Home page, search “Find Jobs”, and search for "R0019512". Complete an application online and see below for documents to attach.

PROCESS FOR EXTERNAL APPLICANTS: Please visit UVA job board https://uva.wd1.myworkdayjobs.com/UVAJobs, "R0019512" complete the application and see below for documents to attach.

  • A curriculum vitae
  • Contact information for three references, (references will only be contacted for those that are short listed)
  • Cover letter
  • Diversity Statement

For questions about the application process please contact Rhiannon O'Coin, Academic Recruiter at rmo2r@virginia.edu

For more information about UVA and the surrounding area, please visit

http://uvacharge.virginia.edu/guide.html.

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

The University of Virginia, including the School of Data Science and Curry School of Education and Human Development 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

The University of Virginia, including 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.

The University of Virginia, including 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.

 

 

 

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Job No:
Posted: 10/24/2020
Application Due: 12/23/2020
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