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Job

Metabolomics and Proteomics Postdoctoral Fellow

The Gordon Lab pioneers advanced mass spectrometry, experimental genetics, and computational approaches to map biochemical networks and functional pathways, and leverages this information for improved therapeutics. Based in the Emory University Department of Pathology and Laboratory Medicine we have ample access to tissue samples, and our affiliation with the Winship Cancer Center Discovery and Developmental Therapeutics Program supports translation of our research into therapeutic approaches.

About the position

The Gordon Laboratory seeks a motivated Postdoctoral Fellow to spearhead cutting-edge metabolite ID and protein interaction studies focused on ovarian cancer diagnostics and mechanistic studies. Ovarian cancer is among the most fatal cancers for women. Since it is often detected at a late stage (Stage 3 / 4), these patients suffer from very poor survival rates, therefore early detection of ovarian cancer is essential for improving clinical outcomes. Ovarian cancer is also characterized by drug resistance, therefore new treatments for ovarian cancer are crucial for improved outcomes. This project will utilize cutting edge metabolomics, proteomics, cell-based assays and computational modeling of molecular interactions. Our goals are to advance ovarian cancer diagnostics, improve mechanistic understanding of ovarian cancer progression, and translate our findings towards next-generation clinical tests and therapeutics.

Apply for this vacancy

What you'll need to apply

Please share CV by email. Title of email should read "Metabolomics postdoc application."

Contact name

David Gordon

Qualifications

Minimum qualifications include:

  • Metabolomics mass spectrometry and metabolomics data analysis

Preferred qualifications include:

  • Cancer model systems (e.g. animal models, organoids, cell culture models, relevant functional assays).
  • Proteomics mass spectrometry and/or proteomics data analysis
  • Biochemistry expertise (e.g. protein interaction studies, HPLC operation, etc.)
  • Molecular biology and experimental genetics (siRNA, CRISPR, PCR, DNA cloning, etc.)
  • DNA sequence analysis (Snapgene, Geneious or other DNA analysis tools)
  • Experience analyzing large datasets