Postdoc: Statistical Genetics & Computational Biology — Independent Research

Statistics Interest Group

Charlottesville (VA)

On-site

USD 52,000 - 65,000

Full time

14 days+
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Job summary

The Chu Lab – Department of Genome Sciences, University of Virginia School of Medicine in Charlottesville invites applications for a Postdoctoral Researcher in Statistical Genetics and Computational Biology. The position focuses on developing deconvolution methods to integrate single-cell references with population-scale RNA-seq for cell-type-specific analyses.

We seek a quantitatively trained scientist with a strong background in statistical genetics and inference, and the ability to publish

Qualifications

  • Ph.D. (or equivalent) in a quantitative field, on or before start date.
  • Strong foundation in statistical inference, Bayesian methods, hierarchical models, or high‑dimensional statistics.
  • Experience with statistical genetics (eQTL, GWAS, colocalization) is highly desirable.
  • Proficiency in scientific programming (R and/or Python).

Responsibilities

  • Develop statistical deconvolution methods to map cell-type-specific eQTLs from bulk and single-cell RNA-seq data.
  • Design and implement new deconvolution frameworks and uncertainty quantification.
  • Pursue independent research directions aligned with lab interests and contribute to peer-reviewed publications.

Skills

Statistical inference
Statistical genetics
R/Python programming
Publications
Single-cell & bulk RNA-seq

Education

Ph.D. in Statistics/Biostatistics/Computational Biology or related

Job description

The Chu Lab – Department of Genome Sciences, University of Virginia School of Medicine in Charlottesville invites applications for a Postdoctoral Researcher in Statistical Genetics and Computational Biology. The position focuses on developing deconvolution methods to integrate single-cell references with population-scale RNA-seq for cell-type-specific analyses.

We seek a quantitatively trained scientist with a strong background in statistical genetics and inference, and the ability to publish

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