Research Engineer

Updated: 3 months ago
Location: Stanford, CALIFORNIA

REQ/POS: 84047 /73120

JCC/Title: 6438/Research Engineer 
Department/DeptId: Medicine / Stanford Cancer Institute

PI Name:Christina Curtis, PhD, MSc Assistant Professor of Medicine & Genetics
3 Years Fixed Term at 100% FTE
Project Description/Role of AS-R:
Situated in a highly dynamic research environment within Stanford University School of Medicine and the Stanford Cancer Institute, the Cancer Computational and Systems biology laboratory led by Prof. Christina Curtis is seeking a highly motivated Bioinformatics Research Associate (Research Engineer). The Bioinformatics Research Associate will be a key member of an interdisciplinary team that leverages high-throughput sequencing of tissue and plasma to study how tumors evolve and evade response to therapy towards the development of predictive and prognostic biomarkers.  He/she will develop and apply bioinformatic and statistical methods to interpret genomic, epigenomic, transcriptomic and proteomic measurements from clinical cancer samples and organoid models and will work closely with a highly collaborative team of molecular, computational and clinical researchers. The successful candidate will have the opportunity to contribute to clinical translational studies and to work with novel technology platforms (including single cell and spatially resolved methods). 
QUALIFICATIONS:
  • PhD in Bioinformatics, Computational Biology, Computer Science or Statistics
  • Experience in the analysis of next generation sequencing data and the use of bioinformatics tools accompanied by a relevant publication record
  • Fluency in multiple programming languages (C/C++, Perl, Python, R)
  • Experience working in a Unix/Linux environment and with high performance computing
  • Excellent problem solving, written and oral communication skills 

 

DESIRED QUALIFICATIONS:

  • Knowledge of cancer genomics and basic molecular biology
  • Familiarity with machine learning
  • Experience with computational modeling and population genetics


Contact information:
cncurtis@stanford.edu
“Stanford University is an equal opportunity employer and is committed to increasing the diversity of its faculty and academic staff. It welcomes nominations of and applications from women and members of minority groups, as well as others who would bring additional dimensions to the University’s research, teaching and clinical missions.”


 
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