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.
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.
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historical documents to modern blueprints and circuit diagrams, from machine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.
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.
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
General syllabus for the Board of the faculty of science and technology
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, firstname.lastname@example.org Professor and Head of Department
Jonas Ekman, +46920-492828, email@example.com
Union representatives: SACO-S Kjell Johansson (+46)920-49 1529
firstname.lastname@example.org, OFR-S Lars Frisk, (+46)920-49 1792 email@example.com
In case of different interpretations of the English and Swedish versions of
this announcement, the Swedish version takes precedence.
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