PhD student in Machine Learning

Lulea University
August 30, 2024
Offerd Salary:Negotiation
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Contract Type:Other
Working Time:Full time
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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.

Machine Learning Research Laboratory is looking for a doctoral student in the field of machine learning. We offer state-of-the-art resources for performing research and a good academic network in Sweden and abroad.

Subject description Machine learning focuses on computational methods by which computer systems use data to improve their own performance, understanding, and to make predictions and has a close connection to applications.

Project description As a doctoral student, you will be 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 The documents will range from historical documents to modern blueprints and circuit diagrams, from machine printed to hand drawn. The project includes developing new techniques, and methods to combine or adapt existing techniques so new classes of historical documents can quickly be recognized. You will work with researchers at LTU and regional and national archives in Sweden. 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 participate in teaching activities.

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 or similar subject. Experience with machine learning, Deep Learning and statistics is required. You must have good knowledge of English in both speech 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 can be added up to 20% of full-time. Starting date on 9 September 2024 or by agreement. Location: Luleå, Sweden.

For further information, please contact: Professor Elisa Barney, +46 920 49 2194 [email protected]

Union representatives: SACO-S Kjell Johansson (+46)920-49 1529 [email protected] OFR-S Lars Frisk, (+46)920-49 1792 [email protected]

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 clicking on the apply button below. The application should include a CV, personal letter and copies of verified diplomas from high school and universities. Mark your application with the reference number below. Your application, including diplomas, must be written in English or Swedish.

Last day to apply: August 30, 2024 Reference number: 2011-2024

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