Scientist Intern - Deep Learning & Computer Vision (Remote)

Cambridge, MA

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Charles River Analytics Inc.
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Posted 1 month ago

At Charles River Analytics, our interns work on real projects and cutting-edge technology. We believe strongly in promoting within, which is demonstrated by the fact that we not only have hired former interns but that several of our Senior Scientists and one of our division Vice Presidents began their careers at Charles River as interns!

This summer, we are looking for enthusiastic Scientist Interns for our Sensing, Perception, and Applied Robotics division. We are seeking students with an interest in innovative technology with an interest in deep learning and computer vision.

You will be working in a small agile group, to develop and apply concepts crossing multiple fields including computer vision, machine learning, signal processing, and state estimation. You will work with tightly-knit, scientists, and engineers to create prototypes of new research concepts that can be further developed into usable products.

Requirements:

  • In pursuit of a B.S./B.A. or M.S. in Computer Science, Engineering or related
  • Expertise in machine learning methods and tools, including deep learning and associated frameworks such as PyTorch/Caffe/TensorFlow
  • U.S. citizenship 
  • Interests in image and/or signal processing methods
  • Ability to work both independently and within a team environment

Additional Skills:

  • Research background
  • Strong verbal and written skills
  • Autonomous systems (e.g. UUVs, UASs, UGSs)

Internship Activities:

Interns at Charles River Analytics can participate in activities such as:

  • Intern challenge problems
  • Seminars
  • Company-wide outings

You can learn more about our internship program here as well as check out our past Great Promise Award (GPA) winners to hear what it is like to be an intern at Charles River Analytics!

Job tags: Caffe Computer Vision Deep Learning Engineering Machine Learning PyTorch Research Robotics TensorFlow
Job region(s): North America Remote/Anywhere
Job stats:  102  13  2
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