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Data Science Internship (Academic Year 2018/2019)

Passionate about making a difference in the world of cancer genomics?

Tempus is on a mission to connect an entire ecosystem to redefine how genomic data is used in cancer clinical settings. With the advent of genomic sequencing, we can finally measure and process our genetic makeup. We now have more data than ever before but providers don't have the infrastructure or expertise to make sense of said data. Here at Tempus, we believe the greatest promise for the detection and treatment of cancer lies in the deep understanding of molecular activity for disease initiation, progression, and efficacious treatment based on the discovery of unique biomarkers.

We're looking for data science interns who are passionate and focused on developing state of the art techniques to processing and analyzing vast amounts of genomic and molecular data. Data scientists will collaborate with product, research and business development teams to develop the most advanced data fusion platform in cancer care.

Tempus is accepting resumes for paid full-time summer internships (and unpaid internships for students receiving academic credits for internship).

Duties and Responsibilities:

  • Work on reinforcement learning to identify specific effects of specific actions (i.e. drugs) 
  • Help with background research projects
  • Work with machine learning and visualization tooling
  • Independently develop and implement analytical pipelines for use in research and in production.
  • Wrangle large datasets and develop innovative methods for storing and processing data.
  • Deploy computation across multiple cores and nodes, with and without the cloud
  • Interrogate analytical results to resolve algorithmic success, robustness and validity


  • Working towards Master’s or higher degree level, or equivalent experience in statistics, computer science, bioinformatics or related field
  • Python or R experience
  • Quantitative training in probability, statistics and machine learning
  • Classical statistical tools, machine learning algorithms, ensemble methods
  • Analytical development and programming skills
  • Reproducible research methods
  • Database familiarity
  • experience with cloud computing is a plus
  • Experience in genomics is a plus, especially experience with next-generation sequencing data processing and modeling
  • Goal-oriented thinking, great problem solving skills
  • Self-driven and works well in an interdisciplinary team with minimal direction
  • Experience with communicating insights and presenting concepts to a diverse audience
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