Kathryn Roeder






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I began my career as a biologist, but found that every question that interested me could only be answered by solving an even more intriguing statistical puzzle. Thus my career path veered into statistics. However, much of my work, both theoretical and applied, remains motivated by my scientific training.

The collaborative research I have enjoyed most is in the area of statistical genetics and genomics. Right now, a topic that interests me greatly is the use of statistical tools applied to genetic and genomic data to understand the workings of the human brain, and the interplay with genetic variation. My collaborative work is primarily motivated by the goal of understanding the genetic etiology of autism. We develop new tools for the analysis of single-cell RNA sequencing data and other multiomic data. These methods rely on various statistical methods, including graphical modeling, network community estimation and latent space embedding, sparse PCA and high dimensional nonparametric techniques. We aim to develop cutting edge statistical tools based on the latest ideas in statistics and machine learning, remembering that the most satisfying aspect of statistics, occurs when methods we develop are applied to answer important scientific questions.

Postdoctoral Research Scientist position open for July 2022
This is a two year postdoctoral position in Professor Kathryn Roeder's research group, co-directed by Professor Jing Lei. 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. We are looking for highly motivated individuals with a strong background in statistical methodology, and a genuine interest in science and data-driven research.

Applicants must have (1) a Ph.D. in statistics, biostatistics, computational biology, computer science or other related quantitative field, (2) strong computing skills, (3) good communication skills. Apply at apply.interfolio.com/100233.
Computational Biology Department 120x120
UPMC Professor of Statistics and Life Sciences
Department of Statistics and Computational Biology
Carnegie Mellon University
Baker Hall 228B
Pittsburgh, PA 15213
Contact: kathryn.roeder (gmail)
Phone: (412) 268-5775
Fax: (412) 268-7828