A fully funded PhD position is available in my research group at Loughborough University on the topic 'Lifelong learning and shareable models: How to reduce the energy footprint of AI and contribute to a sustainable decarbonised future'. This project will further extend research directions highlighted in our recent paper 'A collective AI via lifelong learning and sharing at the edge' Nature Machine Intelligence, March 2024, available at: https://rdcu.be/dB9zt. Current AI models are not designed to reuse and share knowledge. When conditions change, e.g., data distributions, locations, or platforms, retraining needs to occur from scratch. In some cases, like for foundation models or for complex robotics tasks, the process requires very large amount of data and energy. Recent advances towards lifelong learning and sharable models promise to create a new efficient AI landscape in which machine-learned knowledge can be built incrementally and worldwide with optimized energy use. This PhD project aims to advance the latest lifelong learning and sharable AI models to contribute to reduce the energy footprint of AI. An overview of this emerging field can be found in a recent publication from our group on Nature Machine Intelligence https://doi.org/10.1038/s42256-024-00800-2. The student will be part of a growing group of researchers in machine learning and artificial intelligence in the Computer Science Department with collaborators from Loughborough Business School. Learn more about Digital Decarbonisation. The project is in collaboration with the co-supervision of Dr. Vitor Castro, Dr. Rebecca Higginson and Prof. Tom Jackson.