ASSOCIATE IN RESEARCH
Durham, NC, US, 27710
Summary
The position will contribute to two complementary research projects. In the first project, the appointee will develop a computational framework to identify low-quality cells that exhibit cross-modality mismatches in single-cell multi-omics data. In the second project, the appointee will develop a statistical methodology for integrative analysis of multi-sample single-cell multi-omics data.
Job Duties
The appointee will lead the design and implementation of novel computational and statistical methods for single-cell multi-omics analysis. Responsibilities include developing a robust framework to detect low-quality cells exhibiting cross-modality inconsistencies, as well as creating scalable statistical methodologies for integrative analysis across multiple samples. The appointee will build, document, and maintain associated software packages, curate and preprocess large-scale real-world datasets, and conduct comprehensive benchmarking to rigorously evaluate performance across diverse experimental settings. In addition, the appointee will apply these methods to investigate gene regulatory programs related to aging and cellular senescence, ensuring reproducibility, scalability, and broad applicability of the developed approaches.
Minimum Requirements:
Master’s degree in statistics, biostatistics, or a closely related quantitative field, with demonstrated expertise in genomics, computational data analysis, and scientific programming.
Other
- Full-time, 12-month position with possibility of renewal
- Remote
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