Bayer seeks a high energy intern in Bioinformatics, who is ready to explore new challenges, embrace new experiences and learn while taking on increasing responsibilities.
This individual will work in Bayer”s Precision Cardiovascular Lab located at the Broad Institute, and will be assigned interesting, challenging projects dealing with computational analyses of single-cell sequencing data. Ideally, the candidate will have a strong interest in learning about single cell sequencing data analyses, programming in Python/R, working on high-performance compute clusters, and cloud computing, machine learning and/or contemplating a career in Research and Development within the pharmaceutical industry.
The primary responsibilities of this role, Bioinformatics Intern, are to: 

  • Analyze and interpret of single-cell sequencing data from cardiovascular system;
  • Aid in improving tools for primary analyses: pre-processing data from raw data to gene-expression quantification and Secondary analyses: implement of computational methods for benchmarking, improving marker/cell-type identification, and pathway;
  • analyze for downstream analyses of single-cell sequencing data in cardiovascular systems;
  • Document and communicate of results in group meetings, and publication of results as poster/papers if applicable.

Your success will be driven by your demonstration of our LIFE values.  More specifically related to this position, Bayer seeks an incumbent who possesses the following:
Required Qualifications:

  • Enrolled as a full-time PhD student in an accredited U.S. college or University; with a focus in Statistics or Data Science;
  • Fluent in Python or R;
  • Be able to work full time (40 hours per week) in the summer of 2020
  • Strong written and communication skills;
  • English as working language in this highly international environment;
  • Excellent team spirit & presentation skills along with the ability to work in a dynamic, interdisciplinary team environment with strong focus and ambition.

Preferred Qualifications:

  • Experience with single-cell sequencing data analyses.


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