At the Nokia Bell Labs office in Cambridge (UK) we are looking for
bright and motivated students to join our Summer 2019 internship program
and work with us on exciting problems.
We have openings for 2019 Summer internships in our Pervasive Systems
Department with projects in the areas of Internet of Things, Mobile
Systems, Embedded Machine Learning and Radio Sensing.
See below the list of open projects for this year. We will accept
applications until February 15, 2019.
*Human Sensing with Earables*
Study of the algorithmic and system challenges for a custom earable
sensing platform. Focus on behavioural recognition scenarios.
Skills Sought: Prior multi-modal sensing experience (audio, motion, RF
sensors); Strong systems skills.
*Wearable + Server-less AI for Human Sensing*
Study of the algorithmic and system challenges for building a
collaborative sensing solution with wearables and edge devices. Focus on
Skills Sought: Strong systems skills; Backend technologies, Basic ML
*Battery-less Wearables for Human Sensing*
Exploration of a battery-less wearable sensing platform and applications
for physical activity recognitions.
Skills Sought: Hardware prototyping skills, Embedded SW development;
Basic ML understanding.
*Robustness of Deep Sensory Models*
Exploring domain adaptation and generative modelling techniques (e.g.,
GANs) to improve the robustness and generalisability of deep models to
new operating scenarios.
Skills Sought: Advanced skills in at least one deep learning framework
(Tensorflow, Pytorch, Keras); Knowledge of audio and speech processing.
*Hyper-local Conversational Agent*
Developing a context-aware and intermittent commutation framework for
opportunistic multimodal interaction with physical space using mobiles
Skills Sought: Mobile/embedded computing, Layer 2+ knowledge on WLANs.
*On-device Always-on Continual Learning for Personal-Scale Sensory
The project will focus on the development of a lightweight system for
embedded/mobile devices capable of processing and adapting to streaming
data and tasks locally on-device without offloading.
Skills Sought: Machine learning; Experience with TensorFlow or PyTorch.
*Learning Algorithms for Radio Sensing*
What benefits can machine learning offer across the wireless stack for
human sensing? We want to find out, starting with physical measurements.
Skills Sought: Machine learning experience; Applied mathematics and
statistics. Familiarity with software-defined radio a plus.
If you are interested, write to Alessandro Montanari stating your