Postdoc 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 in sustainable machine learning are focused on developing Edge AI solutions that harmonize environmental responsibility with technological progress. Central to these initiatives is the transformative potential of Tiny Machine Learning (TinyML) (https://youtu.be/MgqcLCqqjuQ), which allows AI deployment on resource-constrained devices such as microcontrollers, enabling energy-efficient systems across the cloud-to-edge continuum. By leveraging heterogeneous hardware and enhancing software engineering processes and interoperability, these projects aim to create AI systems that are robust, explainable, and widely accessible. Additionally, they prioritize social and environmental responsibility, ensuring that sustainable AI development not only advances technological capabilities but also aligns with long-term societal and environmental welfare.