Scientist or Senior Scientist, Computational Oncology

Job ID:
Job date: 2018-01-21
End Date:

Company : Sage Bionetworks 

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Role : Research Scientist 


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Job Description:
Sage Bionetworks is currently recruiting for computational biologist / research scientists at multiple levels with an interest and strong background in cancer research. This position presents the opportunity to support and lead research teams focused on a diverse set of questions in cancer. Ideal candidates will have a background in pre-clinical and translational medicine, and an appreciation of efforts to incorporate `omics’ data into clinical practice. We are active in a number of disease areas including immune-oncology, colorectal cancer, prostate cancer, NF1 & 2, lower grade gliomas, and large pan cancer studies.

Responsibilities :

  • Support the interaction with external research consortia to develop bioinformatics analysis and visualizations of genomic data in collaboration with clinicians, biologists, foundations and other bioinformaticians in academia and industry.
  • Design, develop, and lead research projects, from inception to publication, in various cancer domains including:
  • Prognostic modeling of patient outcomes
  • Predictive modeling of drug response
  • Analysis of functional screen data e.g. drug response, siRNA
  • Integrative genomic modeling
  • Design and develop algorithms for interrogating and interpreting complex genomic data.
  • Work closely with Sage and DREAM scientists to develop DREAM Challenges around impactful questions in cancer research.
Basic Qualifications :
  • Candidate will hold a Ph.D. in computer science, bioinformatics, or related quantitative discipline.
  • Strong candidates will also be considered holding Masters or Bachelors degree, with 6+ years of significant relevant work experience and strong track records of bioinformatics analysis.
  • Experience working with high dimensional genomic data, such as sequencing data, gene expression, genotype, CNV, sequence and/or data from other high throughput biological technologies.
  • Demonstrated excellence in research with evidence of advancing an area of computational biology.
Additional Skills/Preferences:
  • Professional software development experience, including strong programming skills in a high level language such as Python, R, or Java.
  • An understanding of advanced machine learning or statistical techniques, such as probabilistic graphical models, Bayesian inference, and optimization methods.
  • A passion for open-access innovation.
  • Strong collaboration, teamwork, and communication skills.
  • A desire to change the world and contribute to the elimination of human disease.


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