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Join a leading computational verification initiative

"As someone who is professionally interested in economic research, working in the lab was fantastic exposure to the work being done by some of the brightest minds in the field"
Economics student, class of 2024

We regularly hire for students to work in the LDI Replication Lab, assisting the AEA Data Editor. Most hires are undergraduates appointed as research interns. We do sometimes hire graduate students to the Lab.

Goal: Ensure that supplementary materials for articles in a journal with a replication policy are (a) accessible (b) reproduce the intended results, (c) document results and findings.

Remuneration: An hourly rate commensurate with experience will be offered. Starting wage is $15.25 per hour, up to 10 hours per week while in session; up to 20 hours per week during the summer.

Work description
The American Economic Association (AEA) monitors compliance with its Data and Code Availability Policy, under the leadership of the AEA Data Editor. LDI Replication Lab members will access pre-publication materials provided by authors, and assess how well these materials reproduce the results published in the manuscript or article. The provided materials and instructions will be assessed using a checklist. Authors’ instructions will be followed (if possible), and success or failure to (i) perform the analysis (ii) replicate the authors' results will be documented. Other related activities, such as literature search or tabulation of results, may also be assigned. Team work is encouraged, and activity will be supervised by graduate student or faculty member. Team members must be at ease working in various computer environments (Windows Remote Desktop, local laptops) and software tools (statistical software, Git). This is ongoing work, and conditional on satisfactory work, continued employment (until graduation) is possible and desirable. Student status with Cornell is required.

Requirements
Training is required as a condition of hiring. While employed, attendance (via Zoom) at two weekly meetings is required.

Trainings occur three times a year. Check the schedule at https://labordynamicsinstitute.github.io/replicability-training/. Live attendance should be expected at the posted times, plus some significant self-paced work. Successful trainees will transition to the actual "replicator" activity as soon as adequate skills are demonstrated. Our training success and post-training retention rate is above 90%. Once trained, you will be able to work flexibly, taking into account exams, summer jobs, and other study constraints.

Students are not paid during training. Training is free, but participation is limited to job candidates.

Required Qualifications/Skills/Experience

Some experience with empirical social science data analysis using statistical software is required. Knowledge of at least one of Stata, Matlab, R or SAS is required, as is familiarity with the Windows Desktop environment. Experience with Git and the command line (Linux, Mac, or Powershell) are assets. Applicants must be current Cornell students, residing in the United States.

How to Apply

  1. Log in to Workday: http://studentemployment.cornell.edu/jobs/student-job-and-intern-service
  2. Search for job listing WDR-00040785. You must be logged in to apply.
  3. To ensure consideration, you also must complete the following form: https://forms.gle/xtXTCdDgTsnZRvuD6.

2020 SOCIOLOGY GRADUATE WORKING FOR A NONPROFIT RESEARCH ORGANIZATION

"[I received] overwhelmingly positive feedback on my documentation method in code reviews, which is all thanks to my time with LDI"

2021 Economics graduate, currently pursuing a Ph.D. in Political Economics

"...The bar to become a replicator is relatively low, so even with my minimal-ish coding experience, I was able to get the job and learn how to actually structure/write good R/Python/Stata code....  I feel like [LDI Replicator position] was the single most important thing I did at Cornell to prepare myself to succeed in [predoctoral fellowship]...."

2020 SOCIOLOGY GRADUATE WORKING FOR A NONPROFIT RESEARCH ORGANIZATION

"[I have] learned a lot about reproducibility” in ways that “really helped me as a research assistant”

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