Luleå University of Technology is in strong growth with world-leading competence in several research areas. We shape the future through innovative education and ground-breaking research results, and based on the Arctic region, we create global social benefit. 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 currently have 1,840 employees and 17,670 students.
In the coming years, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several of these cutting-edge research projects and in the societal transformation that they entail. We offer a broad range of courses and study programmes to match the skills in demand. We hope that you will help us to build the sustainable companies and societies of the future.
Luleå University of Technology is experiencing rapid growth producing world- leading expertise within several research domains. We shape the future through innovative education and groundbreaking research results. From our location in the Arctic region, we aim to create global societal benefit. The Machine Learning Research subject at LTU has an open position available in the area of Sustainable Machine Learning. We offer state-of-the-art resources for performing research and a good academic network in Sweden and abroad. Our machine learning group is part of the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is Sweden's largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of 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 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.
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 PH.D. 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.
Qualifications We seek a highly motivated and enthusiastic PhD student with an MSc degree in Computer Science, Engineering Physics, Electrical Engineering, Data Science, Mathematics, or similar. Fluency in oral and written communication in English is a requirement.
For further information about a specific subject see General syllabus for the Board of the faculty of science and technology
Information Employment as a PhD student is limited to 4 years, teaching and other department duties may be added with max 20%. Entrance to the position: enrolment starting as soon as possible or by agreement. Location: Luleå.
For further information, please contact Senior Lecturer Dr. Hui Han, [email protected]
Union representatives: SACO-S Joanna Hübinette, (+46)920-49 3432 [email protected] OFR-S Lars Frisk, (+46)920-49 1792 [email protected]
Luleå University of Technology is actively working on 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.
In case of different interpretations of the English and Swedish versions of this announcement, the Swedish version takes precedence.
Application We prefer that you apply for this position by, a copy of the master's thesis (if the thesis is not written in English or Swedish, you are asked to additionally submit an English summary of the thesis, 1-2 pages) and copies of verified diplomas from high school and universities. Your application, including diplomas, must be written in English or Swedish. Mark your application with the reference number below.
Final day to apply: 31 October 2024 Reference number: 3441-2024