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Position: Bell Labs Math & Algorithms Co-op

Duration: 3 Months+

Date: Jan to May 2023

Location: Onsite and/or Virtual


Come create the technology that helps the world act together

Nokia is committed to innovation and technology leadership across mobile, fixed and cloud networks. Your career here will have a positive impact on people’s lives and will help us build the capabilities needed for a more productive, sustainable, and inclusive world.

We challenge ourselves to create an inclusive way of working where we are open to new ideas, empowered to take risks and fearless to bring our authentic selves to work.


The team you’ll be part of

Bell Labs

Nokia Bell Labs is the world-renowned research arm of Nokia, having invented many of the foundational technologies that underpin information and communications networks and all digital devices and systems. This research has produced nine Nobel Prizes, five Turing Awards and numerous other awards.


Education Recommendations

The candidate must already have a bachelors degree and also hold a masters degree or equivalent in computer science, machine learning, electrical engineering, operations research, applied math, computational physics or chemistry or similar analytica/computational STEM subjects with an accredited school in the US.


What you will learn and contribute to

We’re looking for student interns who can work collaboratively and regularly with a mentor or mentors to solve a research problem in communication sciences/technologies and/or machine learning in one of the areas listed above and review progress on a regular basis.

 As part of the Theory and Practice of Machine Learning, you will:

  • Analyze deep learning algorithms theoretically and empirically
  • Bulid machine learning solutions to real-world industry problems


What is Nokia looking for from me

For Spring Co-Op positions we would like you to have:

  • Communication theory, signal processing, math optimization, game theory
  • Graduate level understanding of machine learning and associated concepts (latent features, dimensionality reduction, embedding, etc.)
  • Experience with deep learning frameworks such as PyTorch or Tensorflow, and a good understanding of basic deep learning algorithms and neural network architectures
  • Ability to carry out research 


It would be nice if you also had experience with some of the following:

  • Convex optimization and related topics
  • High-level programming languages (Python and/or MATLAB)
  • Modern machine learning methods
  • High-level machine learning packages (Pytorch, TensorFlow, etc)
  • Published research in a scientific conference or journal