Responsibilities for these positions include statistical analysis of epidemiological cohort and nested case-control studies, power and sample size calculations for new projects, statistical programming of advanced methods, and collaborating on the development of statistical and epidemiological methods, if there is interest.
Position involves the development of methodology to handle survival data with dependent selection, such as dependent truncation, and other complexities. Applications are to neurological data, including Alzheimer's disease.
The successful candidate will be expected to conduct empirical research in Alzheimer disease epidemiology and to participate actively in teaching and in the direction of training programs in this area.
This position involves developing statistical methods, data analytic tools, and mathematical models for analyzing smartphone data-collected with our high-throughput digital phenotyping platform-in biomedical research cohorts with the goal of establishing more precise and dynamic disease phenotypes.
These approaches may include population studies using biomarkers derived from metabolic response to radiation, oxidative stress and inflammatory signaling pathways in the cellular response to radiation, genetic and epigenetic mechanisms regulating radiation response, genetic susceptibility to radiation-induced disease in humans, quality of life associated with radiation therapy, as well as environmental exposure to radiation.
The fellow will have access to a wealth of resources including high-quality genomic and epidemiological data, a cutting-edge computing facility, robust analytical pipelines, the most recent sequencing and laboratory technology, and research expertise in genomics, epidemiology, mathematics, and computer science.
Major areas of research include determining the genetic basis of reproductive isolating mechanisms, understanding the role of natural selection in speciation, investigating the role of pollinators in plant speciation and adaption, and using population genetics to untangling the forces of gene flow and selection during local adaptation.
Candidates must have a high level of motivation, demonstrate a track record of consistent publication, have strong organizational, written, and oral communication skills and be able to work both independently and as part of a team.