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QTL mapping, Colocalization and Mendelian Randomization for Alzheimer Disease

Washington University School of Medicine, St. Louis, Missouri

Position Description:

The Cruchaga Lab in collaboration with the GSK Genetics Therapy Area is recruiting a self-motivated, self-driven Postdoctoral Research Scientist to work on QTL mapping, Colocalization and Mendelian Randomization.  Our group generates and analyzes genetic and multi-tissue proteomic data from large and well-characterized cohorts of Alzheimer disease cases and controls.  Proteomic and other omic data (transcriptomics, metabolomics and lipidomics) will be used to perform QTL mapping, Colocalization and Mendelian Randomization to identify novel causal genes, proteins and pathways for Alzheimer disease risk, onset and progression, as well as to create new prediction models and identify druggable targets.   We are seeking a highly motivated researcher with strong analytical skills, especially in Quantitative human genetics and Mendelian Randomization to lead the analyses for these projects.  The new Postdoctoral Research Scientist will join a large team, currently 30+ members, which is led by three faculty members, four postdocs, several PhD students, and three senior scientists.
Recent publications: 
Yang Chengran et al, Nat Neurosci. 2021 Sep;24(9):1302-1312
Laura Ibanez, et al. Genes (Basel). 2021 Aug 15;12(8):1247
Claudia Olive, et al. J Alzheimers Dis. 2020;77(4):1469-1482
Umber Dube et al, Nat Neurosci. 2019 Nov;22(11):1903-1912


  • A PhD in Neurogenetics, Neuroscience, Genetics, Bioinformatics, Computer Science, Data Science, Statistical Genomics, or a related discipline involving the interrogation of ‘omics’ datasets, or expect to obtain a degree in the near future
  • Hands-on experience using PLINK, IBD, PCA, association analyses, R, Bash and excel.
  • Knowledge of PRSice, MAGENTA, MANTRA, Mendelian Randomization Coloc, QTL, SKAT is a plus
  • Solid skills in at least one programming language: R, Python, or Perl and experience working in Linux and/or high-performance cluster environments
  • Familiar with large-scale human genomics or other omics, preferably related to neurodegeneration
  • A strong ability to perform analytical reasoning to extract biological insights from data-driven approaches
  • Familiarity with interrogation of publicly available resources, highly beneficial
  • Exposure working in cross-functional teams
  • Opportunities to participate in translational projects, multi-omic analysis and machine learning approaches

To Apply:

Interested candidates please send cover letter and resume to Oscar Diaz Ruiz, Ph.D., Program Manager. (
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