QuaSSI Predoctoral Program

During the Spring semester, QuaSSI seeks applications from Penn State PhD students for 20-hour per week research assistantship positions as QuaSSI Predoctoral "Fellows" to be taken up the following academic year. Application dates and materials will be posted when available. The positions are designed to facilitate multidisciplinary opportunities for additional training and experience in quantitative and computational methods for social science graduate students (as well as social science methods for graduate students from outside social science). They offer a year during which students may seek additional methods training and work on methods-related research projects, while at the same time being integrated into a diverse set of activities in QuaSSI.

The QuaSSI Predoctoral Program provided the interdisciplinary framework for non-curricular elements of the Big Data Social Science IGERT. Since 2012, most QuaSSI Predoctoral Fellows have also been Affiliates of the IGERT, with some modification of the position details below. 

Ongoing support for the QuaSSI Predoctoral Program is provided primarily by the Penn State College of Liberal Arts, with additional faculty, staff, and infrastructure support from the Department of Political Science, the Program in Social Data Analytics, the Social Science Research Institute, the Institute for CyberScience, and the Office of the Vice President for Research. Additional support for specific students and projects has been provided by home departments, home colleges, and sponsoring faculty.

Past QuaSSI Predoctoral Fellows

From 2004-2017, QuaSSI has supported 34 Predoctoral Fellows from Political Science (18), Sociology (6) [of those, 5 in the dual-title Demography Program], Psychology (3), Anthropology (2), Statistics (2), Computer Science (1), Kinesiology (1), and Neuroscience (1). 

Details about past QuaSSI Predoctoral Fellows, their research, and their accomplishments are provided on the People page.

Duties

Details vary, but this typically takes the form

  • Pursuit of individual research project with faculty mentor, as proposed.
  • Coursework and other training, as proposed.
  • Offering a number of public events for the QuaSSI community, typically one practical workshop or tutorial in the fall and one research colloquium in the spring.
  • Regular presence and active use of provided space and computational resources in the QuaSSI/BDSS collaboration facility in Sparks Building (the Databasement).
  • Participation in collaborative QuaSSI (and, as appropriate, BDSS) research, education, and outreach activities, as directed by the QuaSSI Director and staff. 

Selection Criteria

The primary selection criterion is the likely value-added of the QuaSSI predoc to the candidate, and secondarily the value-added of the candidate to the QuaSSI mission. 

  • All else equal, students should demonstrate a commitment to quantitative methodology (and social science) as a core part of their graduate training. Examples include pursuing a first or second field in methodology in the political science PhD, seeking the certificate in advanced methods in the sociology PhD, or pursuing the dual-title PhD or graduate minor in Social Data Analytics.
  • Candidates are encouraged to be specific about how they expect their dissertation and other research will be improved and how this might produce tangible improvement in their professional placement opportunities.
  • QuaSSI is particularly interested in applications from students in multiple disciplines, students from groups under-represented in quantitative social science methodology, and international students legally ineligible for BDSS-IGERT funding.
  • Students at all stages of their PhD program are eligible. The ideal timing for a conventional QuaSSI predoc is post-coursework and pre-market, corresponding to 3rd or 4th year in most PhD programs. There are, however, exceptions, including for international and other SoDA students seeking to associate with BDSS-IGERT. 
  • Most QuaSSI Predocs require a partial funding contribution from home departments, colleges, or sponsoring faculty. The details of this need not be confirmed at time of application.