PostDoc/Programmer for NSF Project on Influence in Science

An NSF funded project at the University of Chicago, “Tracing Influence & Predicting Impact in Science,” invites applications for a Postdoc Scholar or Programmer position. The Postdoc or Programmer will be associated with the Knowledge Lab in the Computation Institute at the University of Chicago (www.uchicago.edu), one of the leading research universities in the United States. Each position will be for 3 years, contingent on annual reappointment.

This project develops new measures and models that assess and predict the impact of academic research on science, technology, and the public. Building on progress in the measurement of scientific and technological novelty, as well as phylogenetic models of evolution, advances in computational language understanding, and the increasing electronic availability of historical and contemporary scientific texts, this project creates computational tools to identify scientific claims, embed them in their historical, conceptual, and geographical context, and thereby provide a multidimensional evaluation of the nature and scope of their impact. Claims extracted from text will be complemented by article citations and unpublished expert opinions about paths of scientific influence, elicited through interactive online games. Taken together, these data provide the input for probabilistic models that exploit patterns in the structure of scientific language, the graph of citations, and expert opinion to assess the evolutionary and ecological importance of particular concepts and claims, articles and journals, scientists and institutions within the unfolding network of scientific and technical innovation. Our initial focus will be on the broad field of chemistry and its intersections with biology.

The positions require exceptional skills in computation and interdisciplinary collaboration. The Postdoc or Programmer will work with other grant personnel to analyze influence in the process of creating science and technology. Projects draw on a wide variety of information extraction, dimension reduction and probabilistic modeling approaches. The Postdoc or Programmer will assist in code development, robust data cleaning and analysis pipeline for large corpora and possibly end-user interfaces. We particularly value specific skills in machine learning and AI, text-mining, graphical models, network analysis, and dimension reduction techniques, although applicants needs not have all of these skills to apply.

Minimum qualifications for this position are a MS and 5 years professional programming experience OR a PhD or expected PhD (by Summer 2013) in computer science, informatics, applied mathematics, or related disciplines; strong computational skills; and a record of successful teamwork and collaboration. Preference will be given to candidates with experience in interdisciplinary research and previous experience in relevant areas. Women and members of underrepresented groups are encouraged to apply. An open mind and a record of successful teamwork and the ability to communicate and collaborate across disciplinary lines.

Interested candidates must submit to knowledge.lab.chicago@gmail.com:

1. cover letter, describing your interest in and qualifications for pursuing interdisciplinary research in general and metaknowledge research in particular;
2. curriculum vitae (including publications list);
3. description of your computational skill and experience and a broad career trajectory (max. 2 pages), discussing how those skill will support the work of the network;
4. contact information for three or more scholars who know your work and are willing to write letters of reference;
5. one or more examples of working software you have written.

We will accept applications from January through March 31, 2013 or until the position in filled and plan to interview promising candidates as applications arrive. We expect the Postdoc or Programmer to begin their appointments in or around Summer 2013. Compensation includes a competitive salary and benefits plan.