Roche Postdoctoral Fellowship (RPF), Cancer Immunotherapy, Reverse Translation Data Scientist

Location
Little Falls, New York (US)
Salary
$82,000
Posted
August 11 2021
Position Type
Full Time
Organization Type
Pharma

Roche Pharma Research and Early Development (pRED), an industry leader in pushing the boundaries of the sciences in drug development, is committed to develop more personalized healthcare solutions at lower cost to society. In order to continuously deliver more efficacious cancer immunotherapy, pRED is constantly utilizing all the data collected from all current and past clinical trials to maximize the learning of our drugs and to drive fully data-driven decision making. One of such reverse translational efforts aims to establish clinically-relevant knowledge about immune escape mechanisms in cancer. We are looking for a passionate postdoctoral research fellow who will help us push the boundary of response to cancer immunotherapy through  integrating OMICs data and applying advanced analytics and machine learning.  In this postdoc position, you will have the opportunity to:

  • Work directly with biomarker scientists to benefit both future clinical trials and the patients 
  • Share your discoveries and propose new hypotheses on cancer immunotherapy with the cancer research community through publications.
  • Work with a vibrant global data science to learn to implement production-level analysis pipelines and libraries for clinical data.

We are looking for a highly motivated individual who has a passion for driving science through technology, spirit of teamwork, and excellent communication skills that will thrive in a multidisciplinary team to deliver best results. A successful candidate will have some of the following skills or experience:

  • Ph.D. degree in Bioinformatics, Computer Science, Biostatistics, Applied Mathematics, Applied Physics or related discipline.
  • Experience in analyzing multimodal OMICs data from cancer immunotherapy patients
  • Knowledge about immunology, tumor immunology and / or tumor biology and genetics
  • Proficiency in Python and R

     

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