Bell Labs France Math

Il y a 2 mois

Massy, France Nokia Temps plein

Join us in creating the technology that helps the world act together

We are a B2B technology innovation leader pioneering the future where networks meet cloud. At Nokia you will have a positive impact on people’s lives and help build the capabilities needed for a more productive, sustainable, and accessible world. 


Be part of a culture built on an inclusive way of working where we are open to your ideas, you are empowered to take risks and are encouraged to be fearless in bringing your authentic self 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.

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 development of deep language models.

The Mathematics and Algorithms group is spread over 3 countries (USA, France and UK), this offer is for the position in France.

What you will learn and contribute to

As part of our team, 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. Analyze deep learning algorithms theoretically and empirically Build machine learning solutions to real-world industry problems

Your skills and experience

Education Recommendations

Currently, a master2 student 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 France.

What is Nokia looking for from me

We expect you to have:

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

It would be desirable for you to have

Basic understanding of machine learning and associated concepts (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 More specifically, experience/knowledge with training or finetuning Language Models. Interns are encouraged to engage in the writing of final results in scientific papers

Why we're awesome

Nokia offers flexible and hybrid working schemes, continuous learning opportunities, well-being programs to support you mentally and physically, opportunities to join and get supported by employee resource groups, mentoring programs and highly diverse teams with an inclusive culture where people thrive and are empowered.

Company Culture: We believe our people are our greatest asset and we aim to foster a fun, challenging, positive, and inclusive work environment. We offer 1-on-1 mentorship, learning and development opportunities, global impact and interaction, and flexible work/life balance.

Meaningful Co-op Term: During your co-op term, you will have the opportunity to test out the latest technologies and work on innovative projects that could leave a global impact. You get to use skills learned in the classroom and apply it to real work situations while gaining professional hands-on experience.

Nokia is committed to inclusion and is an equal opportunity employer

Nokia has received the following recognitions for its commitment to inclusion & equality:

One of the World’s Most Ethical Companies by Ethisphere Gender-Equality Index by Bloomberg Workplace Pride Global Benchmark

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