Luleå University of Technology is growing rapidly with world-leading expertise in several research areas. We shape the future through innovative education and groundbreaking research results, and based on the Arctic region, we create global social benefits. Our scientific and artistic research and education are conducted in close collaboration with international, national and regional companies, public actors and leading universities. Luleå University of Technology has a total turnover of SEK 1.9 billion per year. We are currently 1,840 employees and have 17,670 students. In the coming years, billions of kronor will be invested in Norrbotten and Västerbotten in major projects aimed at a more sustainable society nationally as well as globally. Luleå University of Technology is involved in several of these highly topical research projects and the social transformation that follows. We have a wide range of programs to match the skills that are in demand. We hope you will help us build the sustainable businesses and communities of the future. Luleå University of Technology is experiencing rapid growth and producing world-leading expertise in several research areas. We are shaping the future through innovative education and groundbreaking research results. From our location in the Arctic region, we strive to create global societal benefits. The Machine Learning Research Group at Luleå University of Technology has an open PhD position in the field of sustainable machine learning. We offer state-of-the-art resources for research and a good academic network in Sweden and abroad. Our machine learning research group is part of the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is Sweden's largest ever single research program, a major national initiative for strategically motivated basic research, training and recruitment of researchers. The program focuses on research on artificial intelligence and autonomous systems that act in collaboration with humans, adapt to their environment through sensors, information and knowledge, and form intelligent systems of systems. The vision for WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. Subject description Machine learning focuses on methods by which computer systems use data to improve their own performance, understanding and to make concrete predictions and is closely related to applications. Project description The Sustainable Machine Learning research projects 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 improves 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 the access to AI technologies, enabling a wide implementation in various applications, from smart cities to remote sensing, all with a focus on reducing the overall carbon footprint and promoting ecological responsibility. As a PhD student, you will join our research group in sustainable machine learning. As part of our dynamic research group, you will lead innovative initiatives at the forefront of sustainability and artificial intelligence, driving forward groundbreaking advances with real impact. The PhD position offers full Swedish social benefits to you. Duties and responsibilities A PhD position involves both theoretical and practical work. As a PhD student, you will be trained in scientific work in the form of publishing scientific articles in journals and at national and international conferences. You will also take compulsory and optional doctoral courses. In addition, you may have the opportunity to try out the role of teacher. As a researcher, you will work as a neutral party in many contexts, providing a great opportunity to learn how to run challenging development projects. This PhD position is affiliated with the Department of Computer Science, Electrical and Space Engineering under the funding of the Wallenberg AI, Autonomous Systems and Software Program (WASP). Qualifications We are looking for a highly motivated and enthusiastic PhD student with a Master's degree in Computer Science, Engineering Physics, Electrical Engineering, Computer Science, Mathematics or similar. You should have a good command of English in both speech and writing and have the capacity to work independently as well as in a team. For further information on specific doctoral training, see curricula for doctoral studies in the Faculty of Engineering Information to be provided Employment as a doctoral student is limited to 4 years, teaching and other departmental duties may be added up to 20% of full-time. Start date: employment starts as soon as possible or by agreement. Location: Luleå. For further information, please contact Senior Lecturer Dr. Hui Han, hui.han@ltu.se Trade union representative: SACO-S Joanna Hübinette, 0920-49 3432 joanna.hubinette@ltu.se OFR-S Lars Frisk, 0920-49 1792 lars.frisk@ltu.se Luleå University of Technology works actively with equality and diversity that contributes to a creative study and work environment. The university's core values are based on respect, openness, cooperation, trust and responsibility. How to apply We prefer that you apply for this position by clicking on the application button below. The application should include a CV, a cover letter, a copy of the Master's thesis (if the thesis is not written in English or Swedish, you are also requested to attach an English summary of the thesis, 1-2 pages), as well as copies of verified diplomas. Your application, including degree certificates, must be written in English or Swedish. Please mark your application with the reference number below. Deadline for applications: October 31, 2024 Reference number: 3441-2024