The ManyBabies Project is an effort to build large-scale international collaborations in infancy research, with the joint goals of replication, best practices development, and theory-building. We address the big questions in early development through bringing many labs together to design strong studies, collect big datasets, and conduct state-of-the art analyses. ManyBabies 1 and 1-Bilingual, which we believe to be the largest-ever experimental studies of infant development, are already in progress. More than 50 labs are collecting data on infants’ preference for infant directed speech, with data collection finishing this spring. ManyBabies 2 is currently in the design phase, and subsequent studies are being planned as well.

We are looking for a postdoctoral fellow to assist with the ManyBabies project, specifically in planning, coordination, and data analysis. The position will be based in the Stanford Language and Cognition Lab, under the supervision of Michael Frank but with many opportunities for collaboration with the broader ManyBabies network including researchers on the the governing board. The primary research focus of this position is the development and application of statistical analyses to the rich and multi-faceted datasets emerging from the ManyBabies project. Funding for this position is guaranteed for two years but there is the possibility of extension to a third year pending external funding.

This fellowship offers rich opportunities for the postdoc to establish their own, independent line of research. Some of the following give an idea of the possible areas of investigating depending on the fellow’s specific interests: 1) developing meta-analyses of the target phenomena and advancing meta-analytic methods for theoretical synthesis (following, e.g., some of the tools at, 2) developing computational models of learning and attention using the large ManyBabies datasets involving habituation/familiarization (following work on Bayesian learning models for infancy data, e.g., Frank & Tenenbaum, 2010), or 3) meta-scientific investigations of reproducibility and replicability in infancy.

All applicants to the position are welcome, but ideal applicants will likely have some combination of the following qualifications:

  • Expertise in child development ideally but not necessarily focusing on infancy research;
  • Strong statistical and analytical skills, including regression (especially mixed effects models) and bayesian methods;
  • Experience with meta-science methods, e.g. meta-analysis, p-curve, etc.;
  • Good communication and coordination skills in service of interacting with a large and diverse group of researchers around the world; and
  • Strong programming skills and facility with open science tools (e.g., Open Science Framework, github, RMarkdown or Jupyter notebooks).

Start date for the position is flexible but would be ideally be before September 2018; funds are available now but we are willing to wait for the best candidates.

The ManyBabies project values inclusiveness and encourages candidates that bring personal diversity of all types ot the position. We recognize that many otherwise strong candidates will lack one or more of the skills listed above and are prepared to provide appropriate training opportunities. Stanford is an unparalleled environment for work at the intersection of child development and reproducibility. Weekly seminar series in cognition and in development provide opportunities for learning and feedback Stanford also offers many training opportunities in statistical and computational methods through coursework and collaboration. Further, the ManyBabies Governing Board is enthusiastic to interact with and mentor the postdoc as well.

To apply, please send to with subject “ManyBabies Postdoc Application”:

  • CV,
  • Brief coverletter stating interest and qualifications for the position,
  • Links to shared analytic materials that demonstrate qualifications (e.g., github page, OSF link), and
  • Names for 2-3 references.

Application review will begin February 15th