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Submitted documents must have all social security numbers, student identification numbers, and/or dates of birth removed (blanked out, blackened out, made illegible, etc.) prior to uploading into the application system.
If you have questions, send an email to ARMY-MRMC@orise.orau.gov. Please list the reference code of this opportunity in the subject line of the email.
All documents must be in English or include an official English translation.
The U.S. Army Research Institute of Environmental Medicine Research (USARIEM) is an internationally recognized research center of excellence for the Warfighter performance science and its useful applications. For over 50 years, USARIEM continues to function as a world-class laboratory for environmental medicine, physiology, health, performance, and nutrition research. Research studies are conducted by scientists from four research divisions, working in concert with one another, as well as in collaboration with other world-class scientists from government, industry and academia. Research divisions are: Biophysics & Biomedical Modeling (BBMD), Military Nutrition. The selected candidate will take part in projects alongside a team of epidemiologists, statisticians and Army personnel. Under the guidance of a mentor, the participant will use big data from the Soldier Performance and Health Database (SPHERE) in order to perform analyses, interpretation and reporting of results from this observational/clinical dataset. This data repository contains demographic, administrative, medical, and performance data from the entire U.S. Army. During the appointment the candidate will be given an opportunity to showcase his/her knowledge and skills by providing assistance on the design, development, execution, and use of statistical and epidemiological approaches for research studies and program evaluation; assisting in analyses and evaluations of methodologies used to ensure the validity and reliability of the analytic output; and participating with team members on data applications, data visualization, and manipulation for computational modeling. Most studies will focus on injury, behavioral health, traumatic brain injury, nutrition, and performance.
Under direct supervision, the candidate will develop and execute original epidemiological research studies. This learning experience will increase knowledge of research design and execution to include retrospective and prospective cohort studies, population level studies, different types of case/control studies and survey studies. The experience will also increase the ability to use data from biological samples, wearable devices, altitude related metrics, negative health outcomes (predominantly injury and behavioral health), biomechanics, and performance; while learning how to using military data and equipment to create military specific products.
For more information about USARIEM, please visit https://www.usariem.army.mil/.
Appointment Length
This appointment is a twelve-month research appointment, with the possibility to be renewed for additional research periods. Appointments may be extended depending on funding availability, project assignment, program rules, and availability of the participant.
Participant Benefits
Participants will receive a stipend to be determined by USARIEM. Stipends are typically based on the participant’s academic standing, discipline, experience, and research facility location. Other benefits may include the following:
Nature of Appointment
The participant will not enter into an employee/employer relationship with ORISE, ORAU, DOD, or any other office or agency. Instead, the participant will be affiliated with ORISE for the administration of the appointment through the ORISE appointment letter and Terms of Appointment.
The qualified candidate should have a doctoral degree in epidemiology, statistics, biostatistics, or a relevant field.
Preferred skills include:
• Prior experience in leading the design and development of epidemiological projects to include statistical analysis plans
• Ability to apply traditional and novel statistical and epidemiological methods to analyze relations between risk factors and health outcomes, including time to event analyses and modeling
• Proficiency in SAS programming language
• Experience with R programming language and SPSS in general
• Experience communicating with scientific collaborators and writing scientific reports
• Experience in using electronic health records (ICD-9/10 codes) for research purposes
• Experience with injury and behavioral health research studies
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