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Assistant Project Scientist, Research Transparency


Seeking outstanding applicants for the position of Assistant Project Scientist for the Berkeley Initiative for Transparency in the Social Sciences (BITSS). The position entails work on an Open Policy Analysis (OPA) research project, as part of the larger BITSS project, in collaboration with Edward Miguel, Oxfam Professor for Environmental and Resource Economics at UC Berkeley. The primary goal of BITSS is to promote transparency in empirical social science research, with downstream improvements in public policy. BITSS identifies, develops, and evaluates strategies and tools that improve the rigor and integrity of research, including study registries, pre-analysis plans, data archiving and sharing platforms, and replications. The project was launched in 2012, and has secured funding to operate through at least 2019.

Closing Date

Dec 19, 2018 11:59 pm PST


The Assistant Project Scientist position will work closely with faculty and apply significant contributions and statistical expertise to a research project that cross cuts multiple social science disciplines. The incumbent will collaborate with Professor Miguel and co-investigators to conceptualize and develop a new set of OPA case studies implemented in close cooperation with government staff in the US and in developing countries. In addition, the position will participate in the design and analysis of various studies that advance research transparency, reproducibility, and Scientific norms. Along this vein, the position will manage research design and data collection, develop statistical models and analyses using Stata, SAS, R and other software packages, and publish resulting findings. The successful candidate will also advise peer researchers on how to improve the transparency of their data and research through conference presentations, trainings, publications, and curriculum development. S/he will advise decisionmakers in multilateral, government, and research institutions on how to mainstream transparent and reproducible research practices in policymaking. Other key responsibilities include: managing data-centric components (including analysis, review and technical assistance) for collaborative research projects and case studies, including developing work plans and timelines to ensure that deliverables are completed on schedule; authoring research papers using data/approaches from "open science" and disseminating findings/best practices to academics, donors and policymakers through meetings and presentations; overseeing and contributing to the development of OPA and BITSS training materials, including development of a graduate-level curricula; contributing to grant proposals, progress reports for current funding sources, and strategic planning for BITSS with relevant stakeholders. The successful candidate will also manage additional research transparency efforts relevant to the PI's goals.

Required Qualifications

Basic qualifications (required at the time of application):

• A PhD or equivalent international degree

Additional Qualifications (required by start date):
• At least one year of post-PhD research experience;
• Experience conducting empirical research including supervising data collection and cleaning activities;
• Competency with statistical software packages such as STATA, SAS, R, to render accurate statistical analysis;
• Experience and competency working with decision makers in multilateral, government, and/or research institutions mainstreaming transparent and reproducible research practices;
• Experience applying data transparency tools and techniques such as study registries, pre-analysis plans, open data platforms, and disclosure of methods and results;
• Experience designing and implementing data collection instruments;
• Experience with independent investigation of solutions to technical and administrative problems;
• Experience working and communicating with teams / colleagues and faculty.

Desired Qualifications

• A PhD or equivalent international degree in Policy Analysis, Engineering, Economics/Business.
• Understanding of key issues related to transparency in empirical social science research;
• Meeting facilitation and discussion of project objectives with academics, policymakers and donors;
• Written and oral aptitude and experience translating complex scientific findings into accessible, non- technical language (eg., via publications or professional presentations);
• Ability to translate complex material/research to broad, non-technical audiences;
• Familiarity with the Open Science Framework and other research transparency tools;
• Specialization in causal inference in applied micro-econometrics, research design and program evaluation;
• Ability to interact with individuals at all levels in a fast-paced environment, sometimes under pressure, while remaining flexible, proactive, tactful, resourceful and efficient, and with a high level of professionalism and confidentiality.

Application Requirements

This is a one-year full-time position with possibility for extension pending funding.

Salary range is $80,000 to $95,500, plus benefits, depending on qualifications. This position will remain open until filled. Please address inquiries to Jeanette Aguilar, HR and Operations Senior Associate, Center for Effective Global Action (CEGA), University of California Berkeley,

To apply, click here
to submit your application and the following required documents:

  1. A cover letter, not more than two pages outlining your interest, intended direction and relevant experience.

  2. A CV listing education and degrees, detailing relevant education and policy outreach experience, and including a full list of publications.

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy, see: