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Guardant Health focused on rare-cell diagnostics
 
   Posted: Thursday, February 07, 2019
 
   
 
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JOB DETAILS
  Company Description

Guardant Healthis a leading precision oncology company focused on helping conquer cancer globally through use of its proprietary blood tests, vast data sets & advanced analytics.The Guardant Health Oncology Platform is designed to leverage our capabilities in technology, clinical development, regulatory & reimbursement to drive commercial adoption, improve patient clinical outcomes & lower healthcare costs.
In pursuit of our goal to manage cancer across all stages of the disease,Guardant Healthhas launched two liquid biopsy-based tests, Guardant360 & GuardantOMNI, for advanced stage cancer patients, & is developing programs for recurrence & early detection, called Project LUNAR. Since its launch in 2014, Guardant360 has been used by more than 5,000 oncologists, over 40 biopharmaceutical companies & all 27 of the National Comprehensive Cancer Network centers.

Job Description

Responsibilities

  • Elucidate genetic & epigenetic signals relevant to early cancer detection from large-scale NGS data
  • Develop reproducible analyses for research & development activities
  • Identify relevant external genomic data sources & Integrate with internal data to improve product performance
  • Interact with medial affairs & technology teams to incorporate relevant biological knowledge to design efficient & relevant experiments
  • Participate in brainstorming sessions, maintain a highly productive & motivating work environment
  • Provide written documentation & specifications

Skills & Experience

  • Dedicated to make a difference in a rapid-paced startup environment
  • Experienced with analysis of genomic & epigenomic NGS data
  • Experienced in visualization of complex experiments to derive biological insights
  • Proficiency with a high level scripting language (R or Python)
  • Cancer biology background a plus
  • Experience with good software engineering practices (e.g., unit testing, code documentation) a plus
  • Experience leveraging AWS based services (e.g., EC2, S3) to speed analyses a plus
  • Familiar with high-performance computing infrastructures (e.g., SGE, Spark) a plus

Education:

Ph.D. in computational biology, machine learning, genomics, or related fields

#LI-LC1

Additional Information

All your information will be kept confidential according to EEO guidelines.

 
 
 
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