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

Nokia is a global leader in the technologies that connect people and things. Powered by the pioneering work of Bell Labs, our research and innovation division, and Nokia Technologies, we are at the forefront of creating and licensing the technologies that are increasingly at the heart of our connected lives. Nokia Bell Labs is internationally renowned as the birthplace of modern information theory, the transistor, the laser and the UNIX operating system.

Bell Labs' research facility in Cambridge is a leading lab working in the areas of Mobile and Wearable Sensing and Systems, Applied Machine Learning, Social Computing and Internet of Things research.

What you will learn and contribute to

We have multiple openings for 2023 summer internships in our Pervasive Systems research department. Students currently enrolled in a PhD or Masters program (Computer Science or Electrical Engineering) are being recruited tor the following projects. Multiple positions are available for each of the following three topics.

COMPUTING ON & AROUND THE BODY

Exploration of the signal processing and machine learning algorithms with wearables to manage health (e.g., monitoring vital signs), improve personal awareness and enhance human hearing.

SKILLS SOUGHT: Sensor Signal Processing, Machine Learning, Embedded Systems.

COLLABORATIVE EDGE SYSTEMS

Study of the algorithmic and system challenges for building collaborative sensing solutions with wearables and edge devices for sensory applications including mobile health, video analytics, and IoT.

SKILLS SOUGHT: Distributed Systems, Embedded SW, Applied ML.

MACHINE LEARNING FOR THE EDGE

Exploration of algorithms and system challenges for data-efficient machine learning on heterogenous edge devices. Topics of interest include, but are not limited to self-supervised learning, federated learning, model adaptation and privacy-preserving ML.

SKILLS SOUGHT: Solid understanding of ML, Knowledge of audio, speech, vision, and sensor data processing.

What we offer