Post-Doc: Science of Data

We seek outstanding candidates for government and philanthropically funded post-doctoral positions exploring the Science of Data at the University of Chicago. Working under the supervision of James A. Evans and Ishanu Chattopadhyay, post-docs will work at the interface of machine learning, social sciences, big data analytics and mathematics applied to diverse empirical domain areas including social systems, biomedical informatics, and financial engineering. 
 
The program aims to go beyond solving individual problems with data, to focus on the intrinsic domain-agnostic principles that might coalesce into a science of data and allow us to investigate how the current data deluge can reshape approaches to scientific inquiry. Such work will involve a deep exploration into topics involving the geometry and topology of data and what these features reveal about underlying social, technological or biological processes that generated it, how these traces can be leveraged for automated, massive data integration, and the induction of arbitrary associations and causal relationships for scientific description and prediction. On the one hand, such approaches should require minimal preexisting knowledge of the system to generate maximal insight. On the other, they should compete with purpose-built data analytics systems on both performance and the generation of insight. Post-docs will interact with members of the University of Chicago’s Knowledge Lab performing work on the Science of Science.
 
Minimum qualifications for this position are a PhD or expected PhD in computer science, informatics, engineering, applied mathematics, statistics or a related fields. The candidate must have a strong background in the theory and practice of machine learning principles, statistical analysis, stochastic processes, and some experience working with large datasets/databases. Proficiency in scripting languages (for example python or julia, and use of machine learning libraries available in python) is required. Familiarity with C++ and use of associated standard template libraries, e.g. STL and Boost, is a plus. 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.