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Department Overview

The postdoctoral researcher will join a collaborative team studying the genetic and environmental factors contributing to the development of attention-deficit/hyperactivity disorder (ADHD), longitudinal trajectories of illness, and outcomes associated with ADHD and related traits. Areas of focus will be the development and application of polygenic risk scores, investigation of mediators (e.g., executive functioning) and moderators (e.g., environment) of genetic risk, and modeling longitudinal trajectories of traits. An overarching goal is the elucidation of causal paths from (1) genes and early environment to (2) trajectories of disorders and dimensional traits and (3) long-term outcomes. Work will be done primarily in a well-characterized, and deeply-phenotyped data set, the Oregon ADHD-1000, collected at Oregon Health & Science University in Portland, Oregon, as well as data from the large, publicly-available ABCD Study. In addition, data from a variety of large-scale genome-wide association studies will be used to construct polygenic risk scores for relevant disorders/traits. Geolocation data/methods will be utilized to construct measures of a variety of environmental exposures.

Function/Duties of Position

• Analysis and write up of data for publication and presentation of data at national and international meetings. 85%

• Conceptualization of data and explanation to others, including data collection staff. 10%

• Attend collaborator, staff, lab, and other necessary meetings. 5%

Required Qualifications

• Ph.D. in Statistical Genetics, Computational Biology, Bioinformatics, Psychiatric Genetics, Psychology, Neuroscience, or other relevant field

• Excellent statistical and computational expertise; experience with R and Python, and techniques for analyzing longitudinal data.

• Background in or strong commitment to content interest in the genetics of mental illness or developmental psychopathology; strong independent writing and speaking skills.

• The ability to work well in cross-disciplinary environment and in a team is a must.

Preferred Qualifications

• Familiarity with GWAS data, polygenic risk scores, Mplus, and/or geocoding techniques is not required, but would be beneficial.

All are welcome