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Location: Pittsburgh, PA

Term: 1 year (with possibility of renewal)

Application deadline: Open until filled

Start date: flexible, but preference is given to a start in January 2019.

We seek two postdocs in computational social science with strong interest,
quantitative skills and expertise in utilizing text and network data to
understand collective behavior and group biases.

We consider a wide variety of disciplinary backgrounds, including
computational social science, computer science (with expertise in machine
learning, natural language processing, etc.), computational linguistics,
social psychology, sociology, political science, and applied mathematics.
The postdocs will work with Yu-Ru Lin and Rebecca Hwa. They would be housed
at the Pitt Computational Social Dynamic (PICSO) Lab. The research project
aims to advance research methodology in revealing biases of different
groups or cultures by analyzing social media data with cutting-edge methods
of natural language processing and statistical learning. Compensation will
be competitive.

Particular priorities for hiring are:  (1) experience in machine learning,
natural language processing (deep learning, distributed semantic
representation, text mining methods), and/or qualitative and mixed-methods
approaches; (2) demonstrated the capability to work with text data,
especially social media data.

Candidates should submit the following materials electronically to Dr.
Yu-Ru Lin at <[log in to unmask]>. Please include "PostDoc Application
2019" in the email subject line.

*Email a single PDF file that includes*

1. A brief statement of interest describing your relevant background

2. Current CV

3. The names and contact information for two references (letters of
recommendation will be solicited from finalists)

4. Two publications or other writing samples

--

Yu-Ru Lin, Ph.D.

Associate Professor, School of Computing and Information, University of
Pittsburgh

[log in to unmask] | web: https://urldefense.proofpoint.com/v2/url?u=http-3A__yurulin.com&d=DwIBaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=JTOngxWQ2fXzTtFf5nOA74ge4DPc3PvJGmkDMxM_D0U&s=j5JqC_xk2Qw4F4ui5RlTxzMp_dBefM76Fwq05WUqmwc&e= | lab:
https://urldefense.proofpoint.com/v2/url?u=https-3A__picsolab.github.io_&d=DwIBaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=JTOngxWQ2fXzTtFf5nOA74ge4DPc3PvJGmkDMxM_D0U&s=SVf36C8UhfAlc_3lxmpV9wLvUQmzv5UsvzUk_vcS_fA&e=

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