"Postdoctoral Research Scholar"

Postdoctoral Research Scholar

Company: North Carolina State University

Job Location: Raleigh, NC

Category: Statistics

Type: Full-Time

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Position Number: 00111581

Essential Job Duties:

We invite applications for a 6-month postdoctoral research fellow to lead and contribute to method development and applied analyses in statistical genomic fine-mapping with a focus on dissecting the genetic architecture of inbreeding depression. The successful candidate will work closely with a multidisciplinary team to develop and apply statistical approaches to locate causal variants and genomic regions responsible for fitness declines associated with inbreeding, using large-scale genomic and phenotypic datasets.

Duties and Responsibilities

• Develop and apply statistical and computational methods for fine-mapping causal variants underlying inbreeding depression, including but not limited to Bayesian fine-mapping, mixed models, haplotype and ROH-based analyses, and rare-variant tests.
• Quantify and partition components of inbreeding depression across the genome.
• Integrate a range data types where available (whole-genome sequence or high-density genotypes, pedigree records, phenotype/fitness measures, transcriptomics/functional annotation) to prioritize candidate loci and interpret biological mechanisms.
• Perform simulations to validate methods and assess power, false-discovery, and effect-size estimation under realistic demographic and genomic scenarios.
• Prepare manuscripts, present findings at group meetings and conferences, and contribute to grant or fellowship proposals.
• Collaborate with lab members and external collaborators; potentially supervise or mentor graduate/undergraduate students for parts of projects.

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Departmental Required Skills:

• PhD in statistical genetics, quantitative genetics, biostatistics, computational biology, population genetics, bioinformatics, or a closely related discipline.

Preferred Experience, Skills, Training/Education:

• Strong background in statistical modeling and quantitative methods (linear mixed models, Bayesian inference, likelihood methods).
• Proven experience working with large genomic datasets (GWAS, sequence, or high-density SNP arrays), and familiarity with runs of homozygosity (ROH), identity-by-descent (IBD), genotype imputation, and genomic relationship matrices.
• Experience with simulation frameworks.
• Good scientific communication skills and a record of peer-reviewed publications or strong

Necessary Licenses or Certifications: n/a

Department: 110701 - Animal Science

Location: Raleigh, NC