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Depending on statistical training, the appointee may develop and apply novel statistical methodology for projects related to Environmental Health (EH), or carry out applied statistical analyses for EH-related projects. The appointee will receive further training in biostatistics and toxicology, and be involved in collaborative work with EH researchers. Interested trainees will have the opportunity to gain experience in community engaged research related to understanding and addressing environmental health problems.
The work will be done under the mentorship of a Biostatistics faculty trainer (Drs. Sally W. Thurston, Matthew N. McCall, Brent Johnson, Tanzy Love, Michael McDermott, David Oakes, or Robert Strawderman) and co-mentorship from a leading Environmental Health researcher.
The specific methodological development or area of application may be based in part on the trainee's interests, and may be motivated by ongoing EH research at UR, such as studies of the effects of exposure to air pollution, metals, endocrine disruptors, pesticides, shale gas (fracking) or stress on pregnancy outcomes, reproduction, immune function, neurodevelopmental disorders, cognitive outcomes, or gene expression pathways. Methodological expertise among T32 faculty trainers includes Bayesian MCMC methods, models for multiple outcomes, latent variable models, measurement error, missing data, causal inference, survival analysis, clustering, statistical genomics, molecular systems biology, and bioinformatics.