Position Description:

The Cruchaga Lab, member of the Neurogenomics and Informatics Center (NGI) at Washington University School of Medicine invites applications for a non-tenure-track faculty position at the rank of Research Assistant Professor to develop a project to identify novel genes and pathways in Early Onset Alzheimer’s Disease utilizing Whole Genome Sequencing (WGS).

Characterization of the genetic topography of Alzheimer’s disease provides a unique opportunity to understand the disease. Genomic studies of AD have primarily focused on patients affected by the late-onset form of the disease (>65), or by the early onset AD (EOAD, <65) from families with Mendelian mutations in the APP, PSEN1, and PSEN2 genes. Mutations in these three genes only explain ~10 percent of cases. Recently Dr. Cruchaga in collaboration with investigators at Miami and Columbia Universities are teaming up in a large effort to generate and analyze WGS in more than 3,500 EOAD cases and more than 10,000 controls from the Alzheimer Disease Sequencing Project. The researchers are looking for investigators with expertise in whole-genome data, co-localization, Mendelian randomization, and TWAS/fusion approaches to lead this large effort. The successful candidate will join an already-stablished team that includes senior and junior scientists, as well as postdocs and Ph.D. students who will also be involved on this project.


Recent publications on the subject:

Takada LT, et al. Alzheimers Res Ther. 2022. PMID: 35932032  ǀ Timsina J, et al. J Alzheimers Dis. 2022, PMID: 35871246  ǀ  Cruchaga C. Med (N.Y.) 2022, PMID: 35590152  ǀ  Ibanez, L. Genes (Basel). 2021. PMID: 34440421



  • Responsible for developing end-to-end a project dissecting the genomic etiology of AD and related phenotypes
  • Lead, develop, and troubleshoot specific analyses
  • Multi-task projects and keeping pace in a dynamic research environment
  • Present research advances at a variety of internal and external seminars
  • Lead manuscript writing
  • Direct, coordinate and supervise laboratory personal
  • Ability to mentor students and research staff.


Preferred Qualifications:

  • PhD or MD with 5 years of postdoctoral experience
  • Prominent record of research achievements in Whole Genome, Whole Exome sequencing
  • Demonstrated expertise in Plink, QC, IBD, PCA, R, Bash, Python, Perl, Java, SAS, SQL, Docker and omic data integration
  • Good knowledge of association analysis PRSice, MAGENTA, Mendelian Randomization, Mantra, Colocalization, Quantitative Trait Loci and Unix/Linux
  • Independent in literature search and keeping abreast of new scientific developments
  • Good, communications and writing skills
  • Demonstrable commitment to diversity, equity and inclusion.


The Cruchaga Lab provides a unique collaborative scientific environment emphasizing the analysis of functional genomics and high dimensional omics data to understand AD and other dementias. The Lab is member of the NGI that includes faculties with expertise in genetics, genomics, multi-omics, machine learning, iPSC, animal models of neurodegenerative diseases and Clinical research. The new faculty member will work in a collegial environment in a well-stablished, well-funded research group, currently 35+ dynamic members, developing bioinformatics tools and analyzing multi omics data to explore the frontiers of AD.


Applicants should submit:

  • Cover letter describing their interest in the position
  • Curriculum vitae
  • One-page description of their single-most important paper highlighting the novelty of the findings (accepted papers only)
  • Names and contact information of 3 professional references.

Please send the materials in a single PDF to the attention of the Search Committee at cgleason@wustl.edu.



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About NeuroGenomics and Informatics Center, Washington University School of Medicine

The NeuroGenomics and Informatics Center is a multidisciplinary team working at the forefront of personalized medicine. The goal of the NeuroGenomics and Informatics Center is to understand the biology of neurodegeneration by using high-dimensional omic data and functional genomic approaches. We leverage these approaches to identify novel genetic variants, genes and pathways implicated in disease, and new molecular biomarkers and therapeutic targets.