Postdoc in Smart Edge Computing

School of Electrical Engineering and Computer Science at KTH

KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy.

Job description

The project investigates efficient architectures and machine-learning algorithms for edge computing nodes in embedded systems for specific applications in medical, healthcare, automotive, and robotics domains. Such edge computing nodes appearing in various sensor networks and IoT devices often need to process large amounts of sensor data in real-time and communicate via wired och wireless channels to external devices with high throughput. The problem is especially challenging because of limited resources in terms of area, power, and storage and strict non-functional requirements on predictability and dependability in those embedded computing devices. This calls for innovative architectures on which approximate machine learning algorithms can execute efficiently to perform runtime data analytic tasks such as data filtering, feature extraction, and anomaly detection, etc.

The position includes both research in the project 80% and teaching duties in the department 20%.

More details about the position and the link for application can be found at the KTH position announcement website: https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:409626/w...