The position is part of a collaborative project with the Division of Wood Science and Engineering at Luleå university of technology, whose overall goal is to develop theory and algorithms for image-guided optimisation of the sawline. Specific tasks is to develop and implement physics aware deep neural networks for tomographic 3D image reconstruction with partially unknown acquisition geometry. Prototypes will be implemented as components in ODL (http://github.com/odlgroup/odl) that offers a seamless coupling between frameworks for tomography (ASTRA) and deep learning (PyTorch).
Link with further information: https://www.kth.se/profile/ozan/page/post-doctoral-fellowship-deep-learning-based-3d-ct-reconstruction-in-forestry
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Requirements
Preferred qualifications
Great emphasis will be placed on personal competency.
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The position offered is for, at the most, two years.
A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.
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KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy. Read more here
Type of employment | Temporary position |
---|---|
Contract type | Full time |
First day of employment | According to agreement |
Salary | Monthly salary |
Number of positions | 1 |
Full-time equivalent | 100 % |
City | Stockholm |
County | Stockholms län |
Country | Sweden |
Reference number | S-2023-0640 |
Contact |
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Published | 19.Apr.2023 |
Last application date | 31.Jul.2023 11:59 PM CEST |
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