Post-Doctoral Scientist

George Washington University

Washington, DC

ID: 7059821
Posted: August 27, 2019

Job Description

Job Description Summary:
The George Washington University School of Media & Public Affairs seeks exceptional candidates with a strong background in Natural Language Processing (NLP) for a full-time, academic research position at the rank of post-doctoral fellow. Beginning as early as fall 2019, the position is for a two-year term. The successful candidate will work with Dr. Rebekah Tromble and other researchers on an interdisciplinary, international research project examining the “health” of political conversations on Twitter.

Given the concerns about growing polarization, abuse, and harassment on Twitter, the project will develop four metrics to quantify the “health” of political conversations on the platform. Measures of (1) mutual recognition and (2) diversity of perspectives will examine and diagnose issues that arise when users isolate themselves from those holding differing opinions. Measures for (3) incivility and (4) intolerance will help assess the extent of anti-normative and antidemocratic discourse. In order to classify these measures at scale, the project draws upon computational approaches in NLP and network analysis, combining these with a firm grounding in social scientific theory, concepts, and empirics to better understand how these phenomena impact Twitter users. (Please note that the project is designed to measure these phenomena and their effects, not to flag and “take down” content considered potentially problematic.) The project offers a unique opportunity to work closely with faculty from different disciplines and to engage across academic, tech, and policy sectors in both the United States and Europe. The project is funded by Twitter, with knowledge exchange between academic researchers and the company. However, the research will be conducted independently and the findings distributed publicly.


Design novel directions in machine learning and neural networks for the detection of discourse structures (e.g., turn-taking) and social constructs (e.g. empathy) in various languages.
Conduct standard data science tasks on large data sets (e.g., data wrangling).
Support other areas of the project research, including statistical analyses, as needed.
Along with the principal investigator (PI), co-supervise research assistants.
Perform other related duties as assigned. The omission of specific duties does not preclude the supervisor from assigning duties that are logically related to the position.
Minimum Qualifications:
Qualified candidates will hold a PhD in a related discipline. Degree must be conferred by the start date of the position.

Additional Required Licenses/Certifications/Posting Specific Minimum Qualifications:
Preferred Qualifications:
Ph.D. in Computer Science, Computational Linguistics/NLP, Machine Learning, Statistics, Data Science, or related fields.
Excellent programming skills in Python. Additional languages (C++, R) are a plus.
Knowledge of current neural network models and implementation tools for neural networks (e.g. Dynet, Tensorflow, Keras, PyTorch, etc.).
Publications in the field of Computational Linguistics/NLP.
Interest in social scientific approaches and methods. Previous experience is a plus.
Strong communication skills.
Ability to work in a highly collaborative and interdisciplinary environment.


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