Position: Bell Labs Math & Algorithms Intern
Number of Position(s): 5
Duration: 10 Weeks
Date: June 2 to Aug 8, 2025
Location: Hybrid
 

The team you'll be part of

Mathematics and Algorithms Group

We're a team of applied mathematicians and computer scientists working on machine learning fundamentals as well as applications to communication systems and services.  Our research spans information/communication theory, mechanisms for self-organizing networks, and AI/ML in services including the development of deep language models.

Education Recommendations

Currently, a candidate for a Ph.D. degree in communication theory, machine learning, or optimization with a minimum of a master's degree or equivalent in computer science, applied mathematics, electrical engineering, operations research, computational physics or chemistry, and other related STEM subjects with an accredited school in the US.

 

We expect you to have:

Strong analytical skills Clear written and spoken communication skills Ability to carry out independent research

For  A1 team, it would be necessary for you to have a good background in 

Wireless communication theory Convex optimization and related topics High-level programming languages (Python and/or MATLAB) Modern machine learning methods Machine learning packages (Pytorch, TensorFlow, etc) Published research in a scientific conferences or journals

For the A2-A3 team, it would be necessary for you to have

Deep understanding of machine learning and associated concepts (features, dimensionality reduction, embedding, autoencoders, etc.) A good understanding of deep learning algorithms and neural network architectures Experience with deep learning computing frameworks/tools such as PyTorch or Tensorflow Strong familiarity with LLMs and VLM

Interns are encouraged to engage in the writing of final results for scientific conferences.

 

We have 3 teams who will host interns in the summer. 

As an intern in any teams A1, A2 or A3 (see below), you will:

Work collaboratively with a mentor or mentors to solve a research problem in one of the areas listed below. Meet regularly with your mentor to review progress and work on the problem. Digest research literature, and prove analytical results. Carry out and analyze analytical results or simulation-based experiments.