Luleå University of Technology is seeking a PhD student in Sustainable Machine Learning.
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.
Tasks and duties
As a PhD student you are expected to perform both experimental and theoretical work within your research studies as well as communicate your results at national and international conferences and in scientific journals. Most of your working time will be devoted to your own research studies. In addition, you can have the opportunity to try the teacher role. As a researcher, you work as a neutral party in many contexts, which provides a great opportunity to be involved in challenging development projects.
This PhD student position is associated with the Department of Computer Science and Electrical and Space Engineering at the Luleå University of Technology under the Wallenberg AI, Autonomous Systems and Software Program (WASP) funding.
