POSTDOCTORAL POSITION: The Gu Lab seeks to train a postdoctoral fellow interested in new minimally invasive approaches for molecular diagnostics. The ideal candidate will have a sufficient quantitative and computational background to analyze sequencing and high dimensionality data. Expertise with methylome datasets, next-generation sequencing, assay automation, molecular experimental techniques, and biostatistics will be helpful. The candidate will have the chance to gain experience within molecular diagnostics, emphasizing ‘liquid biopsy’ cell-free DNA biomarkers, and next-generation sequencing wet and dry lab techniques. Past applications have historically been related to cancer, prenatal, and infectious disease, but are not limited to these areas.
The Gu Lab is a multidisciplinary team that focuses on developing and translating new molecular technologies to advance less invasive and early diagnostics. We are funded by NIH, Burroughs-Wellcome, and the Stanford Department of Pathology. The lab is in the same building and is closely affiliated with the clinical Molecular Genetic Pathology and Clinical Genomics Laboratories. Dr. Gu is a board-certified Molecular Pathologist in these laboratories. Collectively, we carry the most updated next-generation sequencers, automation, and a large bank of biospecimens to develop and trial cutting-edge diagnostic technologies.
For more information, please visit: cfna.stanford.edu
• Ph.D. or MD/Ph.D. degree prior to starting.
• Preference for expertise with next-generation sequencing or epigenetics with exposure to both the wet lab and dry lab.
• Preference for strong computational/mathematical skills with experience working with large, high dimensionality sequencing datasets, and biostatistics.
• Preference for fluency in shell, python, and R, and a familiarity with standard software packages related to next-generation sequencing, genomics, and epigenetics.
• Track record of productive research through peer-reviewed publications.
• A self-starter, team player, with an eagerness to quickly learn new fields.
• 1-page max Cover Letter on your specific interest in this position and the relevant background
• CV (3-page max)
• Links or Pubmed ID to the most crucial publications where you were a primary contributor
• References: 3 references + contact information