Position Overview

The postdoctoral (postdoc) researcher (postdoc; 1 year with possibility of 1-year renewal): An additional postdoc is needed for the NIH-funded R01 SkyRoCKeT study to support and perform data collection, processing, management, checking, and analysis. The postdoc will also contribute to grants management as needed throughout the project lifecycle in areas such as participant recruitment; participant orientations; drafting such documents as IRB amendments, reports, manuscripts, and/or presentations; and additional responsibilities as needed.

The postdoc will contribute 40 hours per week to the responsibilities as directed by their supervisory team, Drs. Daheia J. Barr-Anderson, Laura Gunn, Trudy Moore-Harrison, and Catrine Tudor-Locke. SkyRoCKeT involves interdisciplinary team-based public health science research. Responsibilities and scheduling may vary from week to week depending on data collection needs and involvement throughout this position. Therefore, it is the responsibility of the postdoc to communicate and confirm their schedule and expectations regularly among the team. Because the study is focused on walking behavior in 6-17 year-olds who are in school during weekdays, then the postdoc may also be expected to work later afternoons/early evenings and/or weekends, adjusting their time off during the week accordingly when/if involved in data collection and/or recruitment.


Specific Responsibilities:
● Complete trainings required for the study team, including (but not limited to):
○ CITI Research Trainings (Good Clinical Practice, Social & Behavioral Research/IRB, Biomedical Research/IRB, Health Information Privacy & Security); Minors on Campus Training; First Aid, CPR, & AED Training
● Perform data collection: This may involve the following: assisting with setting up equipment, ensuring it is calibrated and functioning correctly, preparing the testing environment according to procedural standards, performing anthropometric measurements, administering tests to determine metabolic rates, recording test results, using GoPro camera to record testing protocol, and manually tallying steps
● Maintain accurate records and documentation related to the research study, including downloading wearable device data and forms post-testing, etc.
● Perform data processing, management, checking, cleaning, and analysis in Excel and R
● Participate in grants management activities which may include items such as (though not limited to):
○ Active recruitment of participants, conducting participant study orientations, obtaining participant consent
○ Drafting documents such as IRB amendments, reports, manuscripts, and/or presentations
○ Liaise with representatives/staff in offices across campus such as the IRB, post-award, HR, etc.
● Assist in training junior staff to ensure consistency in results during testing and to achieve high-quality data acquisition
● Attend full study team meetings twice/week and any additional sub-team meetings specifically regarding issues related to data collection, etc.
● Attend weekly data management meetings among study postdocs and Dr. Gunn to discuss and address data management and statistical analysis
● Contribute to collaborative team discussions regarding issues that may arise throughout the study, experiences with participants, study progress, etc.
● Participate in additional projects related to research dissemination, including (but not limited to) literature reviews, validating video recordings, or conference abstract submissions
● Other duties as needed/assigned

Required Qualifications

Completed doctoral degree in Public Health, Exercise Science, Kinesiology, Biostatistics, Epidemiology, or closely related areas

Some analytic programming/coding skills for data management and statistical analyses

Interest in learning about quantitative methods applied to inform public health physical activity guidelines

Collegiality within an interdisciplinary team and can work well both collaboratively and independently

Strong intellectual curiosity

Attention to detail

Work flexibility with some availability in later afternoons/evenings and weekends for data collection, adjusting your time off accordingly

Preferred Qualifications

Prior primary data collection experience, particularly in the area of physical activity

Strong computational and analytical skills

Experience programming/coding and/or performing statistical analyses in R

Great communication skills

Ability to successfully multitask and work in fast-paced environments