"Special Faculty Post Doctoral Researcher"

Special Faculty Post Doctoral Researcher

Company:
Carnegie Mellon University

Job Location:
Pittsburgh, 15213

Category:
Statistics

Type:
Full-Time

Carnegie Mellon University: Dietrich College of Humanities and Social Sciences: Statistics

Location: Pittsburgh, PA

Description:

The Department of Statistics & Data Science at Carnegie Mellon University is world-renowned for the significance of its contributions to statistical theory and practice and for its outstanding interdisciplinary applied research. The Department is widely recognized for advancing the teaching of statistics and data science and for the excellence of its undergraduate program, which includes a large number of majors as well as popular joint programs in statistics and machine learning, and in statistics and economics.

We also offer two successful Master's programs and a thriving Ph.D. program that attract exceptional students from around the world. In addition, the Department recently launched an online certificate program in data science and supports both summer undergraduate research programs and high school data science camps.

Our faculty members are internationally recognized for their exceptional expertise and have received numerous prestigious awards and honors. Current collaborative research within the Department is advancing fundamental discoveries in neuroscience, cosmology, networks, finance, genetics, public policy, high-dimensional inference, and methods at the intersection of statistics and machine learning. These strengths are complemented by a friendly and energetic working environment.

The Department of Statistics & Data Science invites applications for a full-time, two-year fixed-term Special Faculty - Postdoctoral Researcher appointment. The appointment will run from September 1, 2026, through August 31, 2028.

Duties and Responsibilities: A two-year postdoctoral position is open in Professor Kathryn Roeder's research group. The successful candidate will apply cutting edge methods in statistics and machine learning to solve scientific problems emerging from genetics, using modern large-scale genomics data such as single-cell sequencing data, proteomics, and metabolomics. We are looking for highly motivated individuals with a solid background in statistical methodology, and a genuine interest in science and data-driven research. Skill in programming is essential.

We seek highly motivated individuals with demonstrated expertise in developing new methods, adapting existing methods and a strong record of collaborative research. Candidates must have a background in quantitative health science research in statistical methods and/or machine learning.

Qualifications:

Completion of a Ph.D. in Biostatistics, Statistics, Bioinformatics, or Machine Learning.

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