Doctoral student positions in the machine learning group at Luleå University of Technology.
Subject description
Machine learning focuses on computational methods by which computer systems uses data to improve their own performance, understanding, and to make accurate predictions and has a close connection to applications.
Project description
The research projects on sustainable machine learning focus on using Edge AI and Tiny Machine Learning (TinyML) (https://youtu.be/MgqcLCqqjuQ) to create efficient, low-power models that can operate on edge devices with limited computational resources. By leveraging Edge AI, these projects aim to process data locally, reducing the need for data transmission to centralized servers, which in turn lowers energy consumption and latency. TinyML further enhances sustainability by enabling the deployment of machine learning models on microcontrollers and other highly resource-constrained devices. This approach not only minimizes the environmental impact of AI systems but also democratizes access to AI technologies, allowing for widespread implementation in various applications, from smart cities to remote sensing, all while maintaining a focus on reducing the overall carbon footprint and promoting ecological responsibility. As a PhD student, you will join our Machine Learning group in Sustainable Machine Learning. As part of our dynamic research group, you will spearhead innovative initiatives at the forefront of sustainability and artificial intelligence, driving forward ground-breaking advancements with real-world significance. The PhD position offers you full Swedish social benefits.