Postdoctoral Researcher, Learned Image Reconstruction from Multi-Modality Data

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The Inverse Problems Group
at the University of Oulu is announcing an open Postdoctoral Researcher position on Learned image reconstruction from multi-modality data. The position is located at the Research Unit of Mathematical Sciences, which has an internationally strong position at the forefront of research in its focus areas. The Inverse Problems Group within the Research Unit is a member of the Finnish Center of Excellence funded by the Academy of Finland: CoE in Inverse Modelling and Imaging (

The position is for 18 months and it is part of the Tandem Forest Values research programme, which is funded by the Academy of Finland. The position is aimed to start October 2020.

Subject field and description

The position is part of a bilateral collaboration with researchers at LUT University (Lappeenranta, Finland) and KTH Royal Institute of Technology (Stockholm, Sweden). The overall goal is to develop theory and algorithms for image guided optimization of the sawline in processing of forest logs. The position includes research into theory and development of algorithms for 3D reconstruction from multi-modality measurements, such as X-ray and optical surface scans. The reconstruction step is done in the larger framework of learned image reconstruction, understood as the combination of data driven methods (deep neural networks) and handcrafted physics models. The large-scale nature of the reconstruction problem coupled with the time-critical nature of the use requires algorithms that not only execute fast but also minimize memory footprint.

The research will be pursued at the Research Unit of Mathematical Sciences at the University of Oulu in close collaboration with researchers at LUT University and KTH Royal Institute of Technology. Within the project, you will have access to expertise in forestry and unique processing data from the sawline. You will also benefit from the strong research environments within the Finnish Centre of Excellence in Inverse Modelling and Imaging.


The new postdoc will be responsible for developing research, teaching and supervision of the Research Unit. Teaching duties will be approx. 20% of the working time.


We are looking for a candidate with a PhD degree in mathematical sciences, signal processing, computer science, or computational physics/engineering that has been awarded (or planned to be awarded) before the commencement of the position. The candidate should have a strong background from machine learning or signal/image processing, preferably in the context of image processing or tomographic image reconstruction. The candidate should also have experience from software development in scientific computing using Python and/or C/C++ in the context of machine learning. Finally, a successful applicant must be strongly motivated and have the capability to work independently as well as in collaboration with members of the research group.

Grounds of assessment

Special emphasis will be given to research expertise within the subject field, demonstrated by an international publications record. Pedagogical expertise, including teaching experience, pedagogical training and the skill to create teaching material will be considered. Work abroad and other international experience will be regarded as an asset.


The salary will be based on levels 5 – 6, of the requirement level chart for teaching and research personnel in the salary system of Finnish universities. In addition to the basic salary, the appointee will be paid a salary component based on personal work performance with a maximum of 50% of the basic salary. The full salary is approximately 3,400 – 4,300 euros per month.


Applications, together with all relevant enclosures, should be submitted using the electronic application form by 7th of August 2020. Applications must be accompanied by the following English-language documents:

1) Brief curriculum vitae, compiled in accordance with the instructions of the Finnish Advisory Board on Research Integrity (TENK),

2) List of publications

3) Brief motivation letter summarizing applicant’s professional experience and expertise and describing why the applicant is interested in about this position


Further information

Assistant Professor Andreas Hauptmann, andreas.hauptmann (at)



About Oulu

The City of Oulu is Northern Finland’s largest and oldest city, with a population of over 200,000. Located in the Gulf of Bothnia in the Oulu River delta, the city has good access from anywhere. Oulu is a very safe and family friendly community with one of the highest qualities of life in all of Nordic countries. As the world’s northernmost tech hub, Oulu has a highly educated and innovative workforce and the University has a strong role in the community.

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