Relevant interest areas include, but are not limited to, causal inference, latent variable methods, survey statistics, missing data and methods for longitudinal studies.
The successful candidate would participate in the teaching of biostatistics courses required for the Population Health and Epidemiology graduate programs and in the training of graduate students in Biostatistics, Population Health, and/or Epidemiology, and would collaborate with investigators in the Department of Population Health Sciences.
Candidates should have a PhD in Biostatistics, Statistics, Bioinformatics, Computational Biology, Biomedical Informatics, Computer Sciences, or a closely related quantitative area, and demonstrated ability to work in a collaborative, interdisciplinary environment.
Relevant expertise may include, but is not limited to, high-dimensional inference, data integration, graphical modeling, experimental design, network analysis, statistical genetics/genomics, machine learning, optimization, combinatorial algorithms, and image analysis.
Candidates should have research interests in statistical theory and/or methodology.
Please note: This position does not involve the BMI Department