Components of the online application are as follows:
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. USARIEM’s highly skilled scientist conduct research in Biophysics & Biomedical Modeling (BBMD), Military Nutrition (MND), Military Performance (MPD), and Thermal & Mountain Medicine (TMMD). With the research performed in each division, scientists work in concert with one another and collaborate with other world-class scientists from government, industry, and academia to impact the world of science and medicine.
The candidate will support projects along with a team of epidemiologists, statisticians, and Army personnel using big data from the Soldier Performance and Health Database (SPHERE) to perform analyses, interpretation, and reporting of results from this observational/clinical dataset. While gaining a unique knowledge of military science, the candidate will also learn military protocols on collecting data used to create military-specific products. This opportunity will allow the participant to display knowledge and understanding of SAS statistical programming language and statistical modeling, used in epidemiological studies of different designs, and include various data-types. Under the guidance of a mentor, the candidate will take part in the design, development, and use of statistical and epidemiological approaches for research studies and program evaluation, analyses, and evaluations of methodologies used to ensure the validity and reliability of the analytic output, and collaborate with team members on data applications, data visualization and manipulation for computational modeling. As most studies will focus on injury, behavioral health, traumatic brain injury, nutrition, and performance, the candidate will also increase his/her knowledge in compiling and evaluating data from biological samples, wearable devices, altitude-related metrics, adverse health outcomes (predominantly injury and behavioral health), biomechanics, and performance.
For more information about USARIEM, please visit our website https://www.usariem.army.mil/.
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.
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:
Health Insurance Supplement. Participants are eligible to purchase health insurance through ORISE.
Training and Travel Allowance
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.
An ideal candidate should have a doctoral degree in statistics, biostatistics, or a relevant field with the following preferred knowledge set:
• Ability to design and develop statistical analysis plans for research projects
• Ability to apply traditional and novel statistical and epidemiological methods to analyze relations between risk factors and health outcomes, including time to event analyses, prediction modeling and absolute risk modeling
• Experience in SAS programming language
• Experience in R programming language and SPSS
• Ability to communicate with scientific collaborators and write scientific reports
• Knowledge of electronic health records (ICD-9/10 codes)
• Knowledge of injury and behavioral health research