Post-Doc: “Machine Learning Applied to the Social Sciences”

We seek outstanding candidates for NSF-funded post-doctoral positions in machine learning applied to the social sciences at the University of Chicago and TTIC. Working under the supervision of James Evans and Nathan Srebro, post-docs will explore cutting-edge problems in machine learning applied to the social sciences: the creation of intelligent, interactive surveys and crowdsourcing “games”; the modeling of social and cultural influence; and methods for representing high dimensional knowledge and tastes with robust, low-dimension traces.

Post-docs will be associated with Knowledge Lab (knowledgelab.org) in the Computation Institute (www.ci.uchicago.edu) at the University of Chicago (www.uchicago.edu) and with the Toyota Technological Institute at Chicago (TTIC,www.ttic.edu), an elite computer science institute located on the University of Chicago campus and supervised by James Evans at the University of Chicago and Nathan Srebro at TTIC and Chicago. Positions are for 2-3 years, contingent on annual reappointment.

Our aim is to apply machine learning, active and collaborative learning, matrix factorization, probabilistic (and graphical) modeling methods, to (one of) three broad challenges: (1) the creation of novel, interactive methods and online, crowdsourcing “games” for eliciting information and preferences in the social sciences; (2) modeling influence and impact in cultural and intellectual domains; (3) creating novel representational methods for analyzing and representing high dimensional knowledge and tastes. Applicants are expected to have strong qualifications in machine learning or related fields, and will be introduced to social science research.  They will have the opportunity to work with other post-docs, researchers and students in the social sciences, while being part of the vibrant machine learning group at TTIC.

Minimum qualifications for this position are a PhD or expected PhD in computer science, informatics, applied mathematics, statistics or a related field, with background in machine learning. Women and members of underrepresented groups are encouraged to apply.

Interested candidates must submit to knowledgelab@ci.uchicago.edu: 1) cover letter, describing your interest in and qualifications for pursuing interdisciplinary research; 2) curriculum vitae (including publications list); 3) contact information for three or more scholars who know your work and are willing to write letters of reference; 4) preferably, one or more examples of working software you have written.

Positions can begin immediately. Compensation includes a competitive salary and benefits plan and assistance with relocation to Chicago.