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NLP Research Assistant with Anjali Adukia

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Title: Natural Language Processing (NLP) Research Assistant 

Hours and duration: 37.5 hours per week for at least 10 weeks in Summer 2024

General summary: 

The research assistant will work a minimum of 10 weeks and supporting Anjali Adukia, Assistant Professor and Faculty Director of the MiiE Lab, by completing research tasks associated with the Principal Investigator’s (PI) projects related to economics of education. Projects that a research assistant may work on include but are not limited to using machine-led text analysis and computer vision tools to explore how representation and messages about gender and race in textbooks influence students’ beliefs and educational outcomes, examining restorative justice and socioemotional learning interventions in schools, and examining the effects of colorism in different contexts. 

The ideal candidate would be extremely organized, enthusiastic about empirical research in applied microeconomics and education, have experience with text analysis tools and data management, and be able to work independently to solve problems.  The position is also ideal for someone who has a long-term interest in pursuing research in economics and/or public policy. This position can be useful as a

pathway to graduate school in economics, public policy, education, or related Ph.D. program.

Principal Duties and responsibilities:

  • Assist in a variety of empirical research activities. 
  • Perform statistical and econometrics analysis with R /STATA or Python. 
  • Develop and apply computational tools (ie, sentiment analysis, word embeddings) to analyze texts in Python.
  • Work with large language models to develop text analysis pipelines in Python. 

Knowledge, skills, and abilities: 

  • Strong interest in computational/quantitative social sciences research.
  • Background in economics, computer science, mathematics, statistics, or a related quantitative social science field.
  • Strong background with Python, or R/STATA.
  • Experience in or willingness to learn Git and Midway.
  • Basic knowledge of Machine Learning and NLP techniques required.

Required Materials: 

Please send the following documents to Elisa Chen ( : 1) Resume, including relevant research experience, academic background, and programming skills; 2) Unofficial transcript(s), listing coursework in the quantitative social sciences or other relevant areas; 3) Brief statement (1-2 paragraphs), addressing your motivation behind joining our group.