NIH Data Science to Advance Women’s Health Research

About the role

This postdoctoral research opportunity offers an immersive STEM learning experience within the National Institutes of Health (NIH), Office of Research on Women's Health (ORWH). ORWH's mission focuses on advancing understanding of biological and social factors that impact women's health. For this program, the fellow will apply data science methods and frameworks to enhance the harmonization, integration, and analysis of research and clinical datasets relevant to women’s health, with the aim of identifying emerging areas for future women’s health research and contributing to an artificial intelligence (AI) platform for women’s health.

Responsibilities

• Receive comprehensive training in developing common data elements, harmonizing and standardizing various research and clinical data sources, and applying data standards to improve interoperability across platforms.
• Through active involvement in ORWH data initiatives, including the development of and coordination of menopause-related Common Data Elements (CDEs), gain experience working with NIH data infrastructures, governance processes, and large-scale data science efforts.
• Collaborate with interdisciplinary teams, develop federal partnerships, contribute to the strategic planning and evaluation of data-driven projects, and build proficiency with analytic tools and data science methodologies relevant to advancing women’s health research.

Requirements

The qualified candidate must be 18 years or older at the time of application and should have received a Doctoral degree in one of the relevant fields and demonstrate an interest in women's health research. The degree must have been received within the last five years of the appointment start date. Current graduate students who are nearing degree completion may apply but must have completed their degrees by the start of the fellowship.

Qualifications

A completed application consists of:

• A complete Zintellect profile.
• A program specific application submitted in Zintellect.
• Transcript(s) – Submit a copy of your most recent official transcript. For this opportunity, an unofficial transcript or copy of the student academic record printed by the applicant or by academic advisors from internal institution systems may be submitted to complete the application requirement, if you do not have a copy of your official transcript at the time of application. The transcript or academic record must include the name of the academic institution, name of the student, courses completed/in progress, grades and degree expected/awarded. A copy of your official transcript and/or letter showing proof of your degree may be required prior to starting the appointment. All transcripts must be in English or include an official English translation.
• A current resume/CV, including academic history, employment history, relevant experiences, and publication list.
• One Recommendation - Applicants are required to provide contact information for at least one recommendation in order to submit the application, but up to three are encouraged. You are encouraged to request a recommendation from professionals who can speak to your abilities and potential for success, as well as your scientific capabilities and personal characteristics. Recommendation requests must be sent through the Zintellect application system. Recommenders will be asked to complete a recommendation in Zintellect. Recommendations submitted via email will not be accepted. Recommendations must be submitted before your application can be reviewed.

Skills

The successful candidate will have demonstrated skills in data science, harmonization, and standardization of research and clinical data sources, and proficiency with analytic tools and data science methodologies relevant to advancing women’s health research.

Benefits

The selected candidates will receive a monthly stipend to help offset living and other expenses during this appointment. Stipend rates are determined by NIH officials and are based on the candidate’s academic and professional background. In addition, NIH may provide a health insurance supplement to cover the monthly premium costs if you elect the ORAU/ORISE health insurance plan, as necessary.

Pay

The selected candidates will receive a monthly stipend to help offset living and other expenses during this appointment. Stipend rates are determined by NIH officials and are based on the candidate’s academic and professional background.

Schedule

Fellows are expected to be fully engaged, either in-person, hybrid, or remote. In-person or hybrid location is Bethesda, MD.