Rebecca Sausville

Project focus: The Fellow will elevate the national imperative of Ph.D. professional development by exploring the interconnection of trends related to the future of graduate education and the future of work, and by recommending systems-level changes needed to ensure equitable access to opportunity for all doctoral students across disciplines.

Rebecca Sausville is a Civic Science Fellow with the GradFUTURES graduate student professional development initiative at the Graduate School of Princeton University. In this role, Rebecca is working on several data projects and analyses to better understand the impact of holistic professional development throughout the graduate student lifecycle and develop insights to inform efforts at Princeton and graduate institutions nationwide. She is particularly looking forward to the opportunity to collaborate on data interpretations and projections and program assessments that are student-centered at every level.

Rebecca’s interest in diverse career pathways for doctoral students, as well as institutional and curricular innovations in support of equitable outcomes for all graduate students, was spurred during her doctoral work at New York University (Ph.D., Classics, 2023). Among other graduate fellowships, Rebecca served as the Innovation and Career Initiative Fellow at the Modern Language Association (MLA) through the NYU Public Humanities Initiative in Graduate Education, where she conducted an assessment of the MLA’s previous graduate school professional development initiatives. Previously, she was a lecturer at Brandeis University, where she taught ancient Greek language and history courses. She has also served as a field archaeologist and researcher on projects in Cyprus, Greece, and Italy.

As a Civic Science Fellow, she is interested in developing opportunities for scientific engagement among humanists and social scientists, engaging in questions of equity in civic science, and in bringing her background in the humanities to craft compelling interdisciplinary narratives built on data.