Published: 11/27/2022

 The Luby Lab, a public health research laboratory at Stanford that seeks strategic knowledge to improve health in communities, seeks a research assistant (RA) to support an ongoing randomized controlled trial that delivers intensive technical training on energy efficiency improvements and information about worker incentives to brick kiln owners in Bangladesh. Across South Asia, the brick manufacturing industry is dominated by inefficient kilns that generate enormous quantities of black carbon, carbon dioxide, and fine particulate matter. The pollution released by the brick industry impacts local air quality and health and agricultural productivity, as well as contributes to global climate change. The objective of this study is to identify evidence-based strategies that can reduce greenhouse gas emissions and air pollution from the brick industry. 

The RA will work on data preparation, documentation, and analysis and will work closely with the research team. The RA will have exceptional data analysis, research, organization, and communications skills. 


Data preparation and analysis: 

• Clean, prepare, and organize survey data as it is collected from the field. 

• Assess data quality, including identifying outliers and missing data. 

• Identify systematic patterns in data, as they pertain to data quality. 

• Write code for cleaning, preparation, and data quality checks in R (preferred, or Stata). 

• Assist in conducting statistical analysis, including regression analysis, and preparing publication-ready tables. 

• Assist in producing high-quality data visualizations and graphics. 


• Prepare detailed, clear, well-annotated, and organized code. 

• Create detailed logs of all data quality issues identified. 


• Hands on experience in R (preferred) or Stata is required. 

• Experience working with real datasets is required. 

• Exceptionally strong self-management and organizational skills 

• Detailed oriented and self-motivated. 

• Ability to handles multiple projects at once, meet deadlines, and practice effective time management. 

• Ability to manage assigned tasks effectively and proactively and deliver high quality work. 

• Familiarity with statistical tools such as linear regression is required, and randomized controlled trials is preferred. 

• Coursework in microeconomics, econometrics, and development economics is preferred. 

• Prior work as a research assistant or other programming/coding roles is preferred. 


10 hours per week


To apply, email Jill Mueller,, to indicate your interest.