Luleå University of Technology experiences rapid growth with world-leading expertise within several research domains. We shape the future through innovative education and groundbreaking research results and drawing on our location in the Arctic region, we create global societal benefit. Our scientific and artistic research and education are carried out in close collaboration with international, national and regional companies, public actors and leading universities. Luleå University of Technology has an annual turnover of SEK 1.9 billion. Today, we have 1,815 staff and 19,155 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.
Machine Learning group is looking for a doctoral student in the field of machine learning. We offer well-equipped laboratory facilities for research and a good academic network in Sweden and abroad.
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 As a doctoral student, you are part of a project that aims to explore machine learning methods for document analysis. The documents will range from historical documents to modern blueprints and circuit diagrams, from machine printed to hand drawn. The project includes using machine learning to identify document components and then using grammars and logic combinations to verify the veracity of the detection results. You will work with researchers at LTU and companies operating in Sweden.
You will be based in the Machine Learning group and will be supervised by senior researchers in the Machine Learning group, who are part of the Wallenberg Project on Autonomous systems (WASP). The machine learning group encourages national and international collaboration for the overall development of its researchers.
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.
Qualifications We are looking for a very motivated and enthusiastic doctoral student who wants to conduct state-of-the-art research. You must have a master's degree in computer science, preferably machine learning. Experience in Deep Learning, statistics, and Natural Language Processing is required. You must have good knowledge of English in both spoken and writing and have the capacity to work independently as well as in teams. For further information about a specific subject see
General syllabus for the Board of the faculty of science and technology
Further information Employment as a doctoral student is limited to 4 years, teaching and other departmental duties may be added with max 20%. Starting: As soon as possible or by agreement. Placement: Luleå.
For further information about the position, please contact Professor Marcus Liwicki, +46920-491006, email@example.com Professor and Head of Department Jonas Ekman, +46920-492828, firstname.lastname@example.org
Union representatives: SACO-S Kjell Johansson (+46)920-49 1529 email@example.com, OFR-S Lars Frisk, (+46)920-49 1792 firstname.lastname@example.org
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 service by clicking the apply button below. The application must contain a CV, personal letter 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.
Closing date for applications: September 30, 2022 Reference number: 3118-2022