Connectionists: Postdoctoral Position in How Programming Languages Shape Thought

[Candice Lewis]

Title: Postdoctoral Position in How Programming Languages Shape Thought @
the Knowledge Lab <https://www.knowledgelab.org/>, UChicago
<https://www.uchicago.edu/>



The Knowledge Lab at the University of Chicago seeks to hire outstanding
candidates for a postdoctoral research project with support from the Sloan
Foundation to explore the degree to which programming languages and data
science environments shape how individuals, groups and communities
“think”—how they construct code, analyze data and solve computational
problems together. The project, titled “The Impact of Programming Languages
and Datascience Frameworkson Thinking, Software, and Science" is inspired
by the longstanding Sapir/Whorf Hypothesis that natural languages influence
how speakers think, which has garnered new evidence with computational
methods and large-scale language data. This project involves analysis of
all public GitHub and other code repositories with statistical and machine
learning approaches that generate insights that link programming language
properties to individual and group behavior to coding and analytical
outputs. Based on insights from these large-scale analyses and ongoing
surveys of programming communities, we will generate programming
experiments (e.g., with the Jupyter interface) to test whether discovered
associations are causal—whether changing languages can predictably improve
the efficiency, collaboration, and creativity of coders and
coding communities.



Postdoctoral candidates will design and conduct independent research, in
collaboration with UChicago Professor and Santa Fe Institute external
faculty James Evans, Director of Knowledge Lab, and Gary Lupyan, a
computational psychologist from the University of Wisconsin-Madison.
Candidates much hold a PhD in Computer Science, or have substantial
computational and data science background and a Ph.D. in Statistics,
Applied Math, Sociology or another Social Science, Linguistics,
Informatics, (statistical) Physics or a related field, and a strong
publishing background.



Specifically, the successful candidate(s) will be responsible for managing
and analyzing a massive collection of version controlled source code with
Machine Learning (ML) and Natural language Processing (NLP) techniques.
Candidates must understand and will need to maintain long running web
scraping tasks, via APIs and HTML parsing and have knowledge regarding
the state of the art in NLP (specifically neural language models, context
free grammars and auto encoders), which they will extend to new domains,
primarily programming code. This development of new techniques for
understanding source code will likely benefit from knowledge of compiler
design, static analysis, complex systems and network analysis.
Candidates must have knowledge of Python and experience running large scale
computational tasks on UNIX systems. Proficiency in multiple other
programming languages, including a functional language, would be a benefit.
Positions could begin anytime within the coming year, and as early as
immediately.



To apply, please send CV, cover letter 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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