Postdoctoral Associate

The International Society for Bayesian Analysis; Durham (NC); On-site; USD 50,000 - 70,000; Full time

Benefits offered by this job

Teaching opportunities

Collaboration with leading researchers

Job summary

The Department of Statistical Science at Duke University offers multiple Postdoctoral Associate positions focusing on developing advanced statistical methods for complex data. Candidates are expected to have a strong academic background and publication record, with an emphasis on collaboration and application-driven research.

Qualifications

• PhD candidates in statistics or closely related fields with strong publication records.
• Experience in complex Bayesian modeling and collaboration desired.
• Interest in analyzing large audio and image datasets is a plus.

Responsibilities

• Develop novel statistical methods for high-dimensional and structured data.
• Characterize uncertainty and infer latent structures in data.
• Publish research and develop algorithms for practical applications.

Skills

Statistical modeling

Applied methods development

Collaboration

Analysis of large datasets

Bayesian modeling

Education

PhD in statistics, mathematics, or related field

Job description

Duke University Department of Statistical Science has multiple Postdoctoral Associate positions to work with Professors David Dunson and Amy Herring in developing novel statistical methods for high-dimensional, complex and/or structured data. A particular focus is on inferring latent structure (e.g., clusters) in data, while characterizing uncertainty. Motivating applications include ecology studies of biodiversity, environmental health, infectious disease subtyping, and neuroscience. A particular focus is on developing fundamentally new classes of statistical models, along with associated theory support and efficient computational algorithm development, directly motivated by scientific and medical applications. Research will ideally lead to not only publications in leading statistical journals but also practical algorithms and corresponding code that can be used by scientists in other fields. Ideal candidates will be finishing up a PhD in statistics, mathematics or a closely related field with rigorous technical training and background combined with a strong publication record and proven abilities in applied-driven methods development. Interest and experience in analyzing large audio and image datasets are a plus, as are experience in complex Bayesian modeling and in successful collaboration with researchers outside statistics.
The positions can start anytime and review of applications will start immediately. Teaching opportunities will be available to interested and qualified candidates. Please submit a CV, brief letter of interest and names of 3 or more references to https://academicjobsonline.org/ajo/jobs/17466 .