Computational genomics postdoc

We are seeking a postdoc to lead the development of new computational methods for the analysis of single-cell sequencing data and application of methods to primary datasets.

You: You must be an independent, motivated, creative and enthusiastic individual with a background in statistical genetics, computational biology, or other relevant quantitative disciplines (computer science, physics and math preferred). You should be comfortable applying your technical skills to a new, exciting and ever-changing field by developing software tools and/or partake in the analysis of primary data. A general interest in making fundamental discoveries of how our genomes encode biological function would be helpful. You must be able to interact with experts in other disciplines such as immunology, molecular biology and clinical sciences.

Us: We are a dynamic team based in the Institute for Human Genetics and the Institute for Computational Health Sciences at UCSF. The lab is focused on developing computational and experimental approaches to better understand how our genes interact with our environment to give rise to phenotypic diversity, especially in the context of immune traits. We collaborate heavily with technologists to adapt new techniques to generate primary large-scale population genomics datasets such as RNA-seq and ATAC-seq in bulk and single cells to study human biology with a quantitative emphasis. We have three major goals in our lab: 1) to discover genetic polymorphisms and epigenetic marks responsible for phenotypic diversity such as disease susceptibility and differential vaccine response, 2) to develop computational models based on a combination of primary data analysis and biological insights to map transcriptional regulatory circuitry, and 3) to build software tools and infrastructures to collect, analyze and share genomic datasets.

Qualifications:

  • PhD in bioinformatics, computer science, computational biology, physics, mathematics, statistical genetics or relevant field.
  • Demonstrated previous research experience through at least one first-author publication in a reputable journal.
  • Proficiency in programming (C/C++), scripting (perl/python) and statistical analysis (R).
  • Comfortable handling up to 1T of data!

Contact: yimmieg AT gmail DOT com