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Methodology Faculty Position on Big Data - The Pennsylvania State University

last modified Mar 07, 2014 01:31 PM
The Department of Human Development and Family Studies (HDFS; in the College of Health and Human Development invites applications for an open rank tenure-track or tenured faculty member whose research focuses on intensive statistical modeling techniques applied to large data sets, particularly innovative dynamic data analysis approaches involving intensive repeated observations across multiple systems (e.g., behavior, physiology) and multiple time scales of observation. This search is part of a Penn State Cyberscience Initiative in computation and data-enabled science and engineering. As part of this initiative, we are seeking outstanding faculty who can work across disciplines and in a team to advance methodologies including algorithms, data and software to exploit "Big Data" and “Big Simulations” for scientific studies (see

Some examples of relevant focus areas include: (1) Large-scale simulation studies of parametric dynamic systems modeling techniques and other statistical modeling approaches such as complex multilevel and mixture structural equation modeling. (2) Use of simulation techniques (and empirical data) to articulate models of human behavioral change and development (akin to computational systems biology). (3) Analysis and modeling of massive social-media and sensor data about human developmental and change processes by means of recursive estimation techniques. (4) Use of interactive systems to change behavior and development (e.g., "gamification" of everyday processes in developing intervention paradigms). (5) The analysis of neuro-cognitive data, in particular fMRI data linking the voxel level to the level of brain regions of interest (ROI). (6) Analysis of archival qualitative data (e.g., text analysis of interviews, analyses of videotaped behavioral interactions).

Applicants should demonstrate a clear program of research, strong publication record, and the potential to obtain external funding. Responsibilities include teaching undergraduate and graduate level courses as well as directing theses/dissertations. An earned doctorate in the behavioral or social sciences and the promise of outstanding scholarly accomplishments are required.

Rated by the U.S. News and World Report as one of the top developmental science programs in the country, the Department of Human Development and Family Studies administers graduate, undergraduate, and research programs focused on individual development from infancy to old age, on family structure and dynamics, and on the impact of social/cultural contexts on development and family functioning. The Department`s multidisciplinary faculty includes expertise in development across the life span, social-affective neuroscience, clinical and health psychology, prevention science, family process and intervention, demography, education, and methodology. A hallmark of the program’s research and graduate training is its focus on development and application of innovative methods for the analysis of change over time. These activities are supported by two research groups: The Methodology Center ( and the Quantitative Development Group (

To apply, candidates should submit a letter of application, statements of research and teaching interests, a CV, at least three letters of recommendation, and selected (p)reprints to: Please indicate “Big Data Search” in subject line of email correspondence. If unable to submit electronically, mail materials to Dr. Peter Molenaar, Big Data Search Committee, Department of Human Development and Family Studies, 315 Health and Human Development East, The Pennsylvania State University, University Park, PA 16802. Review of applications and nominations will begin immediately and continue to be accepted until the position is filled. For more information, contact Dr. Molenaar at Employment will require successful completion of background check(s) in accordance with University policies. Penn State is committed to affirmative action, equal opportunity and the diversity of its workforce.