Overview

Salary: $100,000.00 – $150,000.00

Client is seeking a Senior Principal Data Scientist, Sequencing to join their team.

As a principal data scientist in machine learning, you will explore an exciting new application of neural networks.  Your role will involve architecting and training models on proprietary DNA sequencing data, generated by our high throughput single molecule sequencing instrument.  This role will require a firm grasp of signal processing concepts for raw voltage signal pre-processing as well as intuition about model architectures and training.  Due to the complexity of our sequencing instrument and multidisciplinary nature of the team, you will be working directly with scientists from a variety of fields, including physics, biochemistry, electrical engineering and software engineering.

If you are passionate about machine learning, big data, medical diagnostics and challenging scientific research problems we’d like to hear from you!

Responsibilities Include:

  • Model design and training
  • Raw signal preprocessing
  • Application of statistical models to characterize behavior of an ensemble of single molecule sensors.
  • Data exploration and collaboration with scientists from a diverse set of fields to advance our DNA sequencer technology development.

Skills

  • Hands on Deep Learning experience using TensorFlow, Theano or similar
  • Scientific programming experience in Python, especially numpy / pandas / scikitlearn / matplotlib or the equivalent, such as Matlab and C/C++ experience and willingness to learn Python
  • A firm grasp of signal processing concepts
  • Experience with distributed computing or cloud implementation
  • Previous exposure to fields of bioinformatics, natural language processing, or similar

Background

  • Ph.D. or equivalent experience in computer science, information theory, physics, electrical engineering, computational biology, or statistics
  • Demonstrated potential to lead complex, long-term projects
  • Desire to work as part of a team in a startup-like environment

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