Connectionists: Postdoctoral Position in the Science of Teams and Innovation @ the Knowledge Lab, UChicago

[Candice Lewis]

The Knowledge Lab <https://www.knowledgelab.org/> at the University of
Chicago seeks to hire an outstanding candidate for a postdoctoral research
project with support from the National Science Foundation that uses
large-scale data analysis and online team experiments to explore how to
design teams for innovation and success. The project, titled “Understanding
Team Success and Failure” was partially inspired by insight from our own
recent work studying more than 50 million teams in science and technology
that illustrated how smaller teams are much more likely than larger ones to
produce work that disrupts the frontier
<https://arxiv.org/pdf/1709.02445.pdf>. The project is also motivated by
the realization that the vast majority of research on teams exhibits
success bias, where data on failed teams remains under-recorded or
censored. This project will involves a two-stage research program to
understand how successful teams of different sizes and shapes “think
differently” and can be designed to accelerate scientific, technological
and creative discovery, invention and development.

Postdoctoral candidates will design and conduct independent research, in
collaboration with UChicago Professor and Knowledge Lab Director James Evans
<https://www.knowledgelab.org/people/detail/james_a_evans/>, and Dashun Wang
<https://www.dashunwang.com/>, a network scientist and physicist from
Northwestern University’s Kellogg School of Management. Candidates much
have substantial computational and data science background and a Ph.D. in
Sociology, Economics, Psychology or a related Social/Behavioral Science,
Physics, Applied Math, Computer Science, Engineering or a related field,
and a strong publishing background.

Specifically, the successful candidate will be responsible for assembling
data, constructing features and evaluating success and failure outcomes for
millions R&D teams over 100 years in terms of team size, network structure,
role composition and experience. Second, insights developed from this
investigation will enable the candidate, in collaboration with Evans, Wang
and the broader team, to collaborate on the launch of large-scale online
team experiments to isolate the causal mechanisms driving team success and
failure. We will publish the results of analyses and experiments and make
recommendations for policy to design teams optimized for specific purposes,
such as advancing science and technology. Candidates must have experience
with statistical models, inference, and knowledge of experimental design.
Experience with Bayesian inference and machine learning a strong plus.
Candidates should also have extensive experience (2 or more years) with
scientific computing in Python. Positions could begin anytime within the
coming year, and as early as September 2018. Competitive salary & benefits.

To apply, please send CV and names for letters from at least two references
to Candice Lewis, cllewis at uchicago.edu.

Candice Lewis, Ph.D.
Assistant Director
The Knowledge Lab <https://www.knowledgelab.org/>
University of Chicago
5735 S Ellis Ave| Room 221
Chicago, IL 60637
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