Harvard T.H. Chan School of Public Health
About Ariadne Labs
Ariadne Labs is a joint center for health systems innovation at Brigham and Women's Hospital and the Harvard T. H. Chan School of Public Health. Our goal is to drive scalable solutions for better care at critical moments in people's lives everywhere. Better care means better health outcomes, lower costs, and more actual caring. Critical means solving health systems failures that have major impact, typically touching people by the millions.
We seek an early career PhD-level researcher with interest in health systems research and skills in research design, statistics, implementation science, and/or statistical programming. The researcher would join our childbirth team, bringing his or her methodological expertise to bear on our existing data and research endeavors while beginning to carve out an independent area of research within the spectrum of our work.
We are looking for an independent thinker who works well in teams, collaborates well with people from other disciplines, and brings curiosity and high standards to the scientific enterprise. Although the fellow will frequently work independently, s/he will be supported by the BetterBirth team, Ariadne's scientific leadership as well as the Science & Technology Platform (a cohesive team of statistical analytic staff, data architects, research assistants, and program managers).
We welcome applicants with backgrounds in public health, epidemiology, sociology, quantitative psychology, health policy, health services research, statistics, or related fields and a demonstrated interest in maternal and/or neonatal health, particularly around the time of childbirth.
The BetterBirth Program seeks to improve the quality of care, minimize complications and end the preventable deaths of women and newborns during childbirth through effective implementation of evidence-based, scalable solutions at the frontline of care.
Within BetterBirth, existing analytic tasks for the fellow will include statistical analysis and write-up of existing datasets from the BetterBirth Trial (a cluster randomized controlled trial following 160,000 mother-baby pairs). There are over 30 sub data sets and 204 million data points in the data set. BetterBirth is also exploring possible study design and analytic plans for data from 30 sites implementing the Safe Childbirth Checklist across the world.
Here are some but not all of our current research aims. The fellow's independent research would likely fall into one of these areas but we are open to new ideas!
Exploring what the BetterBirth data can tell us about: Timely referral and safe transportation of patients; Provider skills and complications management; Accountability, motivation and incentives amongst providers; Supply availability and use; and Readiness for change.
Exploring intervention redesign for more effective behavior change
Readiness to implement maternal and neonatal health quality improvement at the frontlines of care
Principal duties and responsibilities
Working closely with colleagues, support research projects with methodological and statistical expertise
Construct scientifically rigorous and ethical study designs that meet clinical needs, feasibility requirements, financial constraints, and publication standards
Write and review grant applications, study protocols, manuscripts, and
Develop and carry out analytic plans for existing and new datasets, including diagnostic, descriptive, and inferential analyses as needed
Communicate scientific results in various venues
Collaborate with scientific colleagues on the Science & Technology platform
Mentor research assistants and project coordinators
Contribute to the overall scientific integrity of Ariadne Labs
Required qualifications and skills
PhD (or comparable terminal degree) in public health, epidemiology, sociology, health policy, statistics, or related field
0 - 3 years relevant postdoctoral experience
Statistical programming skills (
, R, or similar package acceptable)
Familiarity or experience with health systems research, implementation science, adaptive trial design, or related methods
Familiarity or experience with data management and
Excellent communication, writing, and data presentation skills in English
Intellectual flexibility, curiosity, and willingness to learn
High level of personal interest in the field of maternal and/or neonatal health or childbirth
Preferred qualifications and skills
Field experience around maternal and/or neonatal health or childbirth
Familiarity with systems science or complex systems
Skill in literature reviews and content synthesis
Experience working in a matrix environment
relations or human subject protections
Data visualization skills
401 Park Drive, 3rd Floor East
Boston, MA 02215
To apply: Please send a CV, cover letter, and writing sample to:
Director of Talent Development
Equal Opportunity Employer:
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
Website : http://www.harvard.edu/
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