Position Description
The Division of Biostatistics at Washington University School of Medicine in St. Louis seeks highly qualified applicants for a full-time faculty appointment at the rank of Assistant Professor or Instructor under research track. Responsibilities include supporting the University’s Knight Alzheimer Disease Research Center (ADRC) and the Dominantly Inherited Alzheimer Network (DIAN) in study design and statistical analyses, authoring and co-authoring publications in Alzheimer disease and aging research and related statistical methodologies, providing statistical support for research grant proposals by investigators from the ADRC and DIAN, and supervision and mentoring of Master’s level statistical data analysts and graduate students in Biostatistics and Data Science. Applicants with experience in aging and neurodegenerative disease research who are interested in the related statistical methodologies such as innovative study design, novel statistical methods in biomarker and imaging studies, and high-throughput and big data analyses are especially encouraged to apply. Members of underrepresented groups are strongly encouraged to apply.
The Division of Biostatistics is housed within the Institute for Informatics, and consists of more than 15 faculty biostatisticians who provide a collegial and vibrant research environment, with a departmental history of mentoring junior faculty biostatisticians. The Division and the Institute are committed to building a diverse and inclusive community where members from all backgrounds can thrive professionally. As part of general faculty responsibilities, participation in Division and Institute activities and meetings as well as departmental, school and university-wide committees is expected. Participation in scientific meetings and scholarly activities to build a national reputation are expected.
Basic Qualifications
Qualified candidates must have a in Biostatistics, Statistics, or related fields of Data Science. Other qualifications include: strong interest in collaborating with biomedical investigators and also independent research on biostatistical methodology, strong training and experiences in longitudinal statistical models and messy data analyses, proficiency in standard statistical software packages (SAS, R, STATA, etc), excellent communication skills, and the ability to work as part of multidisciplinary teams.
Assistant Professor in Biostatistics • St. Louis, MO, US
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