We are Signify, the new company name of Philips Lighting.
We're the world leader in lighting for professionals, consumers and for the Internet of Things. Our passion for sustainability makes us one of the top 10 greenest companies in the world.
Seethrough the eyes of our employees!
Working as a Deep Learning, Sensor Data Fusion Intern at Signify is dynamic. You will work in the area of machine learning for mobile platforms developing new algorithms on data from various sensors in the smart phones/watches to enable interactions with connected lighting system. Towards the end of the internship, you will be expected to share work in the form of a demo and technical report with other colleagues in the group. You will also be working in a team setting with scientists, taking initiatives, and contributing highly innovative ideas. Previous internships in our group have led to several publications and/or patent filings.
This internship role is part of Signify Research located in Cambridge, MA, a center of excellence on Artificial Intelligence and Machine learning Innovation for Signify. The team works together with the Signify global Research, businesses and functions on AI/ML. Its responsibilities are at the heart of driving AI/ML innovations for systems, new IoT propositions, and innovative apps. If you are someone who always comes up with great ideas and ready to use your creative mind to solve practical problems, this internship role may be for you. You will learn and apply new cutting-edge techniques that will be rewarding for your career. With a great freedom to innovate, you will play an active role and grow yourself on AI and ML.
As a Deep Learning, Sensor Data Fusion Intern, you will work from June 7th to August 20th. These are not fixed dates and can be adjusted. This internship could also lead to a full time at-will position
What you'll do
Build an IoT data analytics platform to connect people, lighting, and facility with machine learning algorithms.
Design and develop machine learning algorithms with lighting IoT sensor data
Explore deep learning and probabilistic approaches to fuse image and audio data
Build a real-time demo to fuse data from different modalities for activity and event detection.
What you'll need
Must be able to work in the United States without corporate sponsorship now and within the future.
A graduate-level student (PhD preferred) in computer science, engineering, or other related disciplines. A focus on Bayesian inference and machine learning is highly preferred.
Good software engineering skills with Python is required. Knowledge with Java and/or C is a plus.
Experience with machine/deep learning framework such as SKLearns and Keras. Knowledge with PyTorch, and/or TensorFlow is a plus.
Experience with cognitive psychology, evidence-based design, human factors research
Experience with database including SQL, NoSQL, RDS, etc.
What you'll get in return
Hands-on experience on working with real-world IoT sensor-data
Work with a diverse Research team to apply cutting-edge lighting solutions in a wide variety of applications
Contribute to Intellectual Property (Patents and Trade-secrets) and publish in top peer-reviewed conferences and journals
Opportunity to learn and apply techniques to real world problems.
What we promise
We're committed to the continuous development of our employees, using our learning to shape the future of light and create a sustainable future. Join the undisputed leader in the lighting industry and be part of our diverse global team. #LI-FM1 #WeAreSignify #SignifyLife