Senior Research Associate in Molecular Epidemiology

2 days ago

London, Greater London, United Kingdom University of Bristol Full time
About the Role

We are seeking a highly skilled postdoctoral researcher with expertise in Epidemiology and omics to join our team at the University of Bristol.

Key Responsibilities

  • Advance understanding of genetic and environmental causes of pregnancy complications using Mendelian randomization, GWAS, and genome sequencing studies.
  • Utilize multi-omics (epigenetics, transcriptomics, proteomics, metabolomics) to explore molecular mechanisms and improve prediction of pregnancy complications.
  • Generate research ideas, develop analysis plans, and identify relevant data sources and bioinformatic tools.
  • Clean and analyze large-scale, high-dimensional datasets.
  • Develop analytical tools, pipelines, and repositories.
  • Document and version control all developed code.
  • Write scientific papers and present research findings at conferences.
  • Collaborate with researchers within and outside the University of Bristol.

Requirements

  • Experience in Epidemiology
  • Proficiency in standard statistical methods (e.g., regression models)
  • Experience with genome-wide association studies (GWAS)
  • Proficiency in Linux/Unix operating systems
  • Expertise in R, Python, or other common programming languages

Desirable Criteria

  • Experience with exome or whole-genome sequencing data analysis
  • Expertise in genotype calling and imputation of genotyping array data
  • Experience with additional omics data (e.g., DNA methylation, transcriptomics, proteomics, metabolomics)
  • Experience with electronic health records data analysis
  • Familiarity with high-performance computing on a cluster
  • Experience with Research Analyses Platforms (RAP), such as DNAnexus in UK Biobank
  • Experience developing/sharing open-source code
  • Background in obstetrics or perinatal Epidemiology
  • Publications in GWAS or Mendelian randomization
  • Publications on exome or whole-genome sequencing data analysis

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