Job Posting

Title Postdoctoral Position in How Programming Languages Shape Thought
Company Knowledge Lab, UChicago
Description

The Knowledge Lab at the University of Chicago seeks to hire outstanding candidates for a
postdoctoral research opportunity with support from the Sloan Foundation that explores 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 Frameworks on 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 largescale
language data. Our project involves analysis of all public GitHub and other code repositories using
statistical and machine learning approaches that generate insights linking 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 also 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 Knowledge Lab Director James Evans, and Gary Lupyan, a computational
psychologist from the University of Wisconsin-Madison. Candidates must have substantial computational
and data science background and a Ph.D. in Computer Science, 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 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, will
be a benefit. 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@uchicago.edu.

Location Searle Chemistry Laboratory
URL https://www.knowledgelab.org/
Deadline 30 June 2019
Contact

Candice Lewis
cllewis@uchicago.edu

Tags
Job Type Full Time
Attachment Postdoc_SLOAN.pdf