This person will contribute to two NIH-funded epidemiologic studies of air pollution and dementia risk. The first study, the Air-Noise-Dementia Study (ANDS) examines the hypothesis that long-term exposure to air pollution and noise from the community affect brain changes that we can see on magnetic resonance images (MRI) and, ultimately, the development of dementia. The second study is entitled "Air Pollution and Alzheimer's Dementia: Neuropathologic and Olfactory Mechanisms in Multi-Ethnic Longitudinal Cohorts Dementia" (AERONoSE). This study evaluates olfactory pathways linking air pollution exposure to dementia risk. We will estimate the effect of air pollution exposure on neurocognitive and olfactory outcomes in 5 longitudinal cohort studies, and examine how resultant neuropathology and direct deposition of particulate matter, assessed by advanced microscopy, explains these relationships.
The primary responsibilities of this position will be to:
(1) analyze data from existing epidemiologic studies
(2) write scientific manuscripts to be submitted to and published in peer-reviewed journals; and
(3) contribute to the logistics underlying the operations of these studies.
Duties will involve literature reviews; managing, cleaning, and coding data; analyzing data in SAS or R; developing and contributing to a system of standard analytical procedures and guidance for the projects; interpreting and presenting data in tabular or graphical form; engaging in technical checks of programming; presenting results at scientific research conferences; drafting manuscripts for journal submission; and assisting with the writing of research grant proposals. As appropriate and needed, the person in this position may be involved in the following activities: informal mentoring of more junior scientists; managing IRB protocols, coordinating and track data use agreements; scheduling group meetings; acting as liaison to data and specimen managers at collaborating sites; and developing and maintain a system for tracking progress toward the study aims.
Applicants should have strong communication and writing skills, along with experience in the analysis of repeated measures longitudinal data and in causal methods in epidemiology (e.g., marginal structural models). Candidates should hold a PhD or equivalent doctoral degree in epidemiology, biostatistics, or a closely related field. Candidates holding a masters degree in biostatistics or epidemiology, along with five years of experience relevant to the duties above, will also be considered. (Note that degrees in data science or data analysis will not be considered without specific training and/or experience in epidemiology.)
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