Lund University, Faculty of Engineering, LTH, Matematikcentrum, LTH

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Work Duties
Programming and development of machine learning algorithms for smart systems.

The position is financed by the project ”Semantic Mapping and Visual Navigation for Smart Robots”, which is financed by the Swedish Foundation for Strategic Research.

The goal of this project is to develop an integrated framework for the next generation of autonomous vehicles that can see, navigate and map using computer vision and optimal control. Traditionally visual processing is built on independent solutions for object detection and 3D scene reconstruction, while there does not exist any single integrated modelling toolkit. One example is multi view geometry, where systems for automatic reconstruction of large scene 3D models from a number of 2D images have been developed in recent years. Though, the methods are purely geometric, passive, and use no semantic scene understanding. The limitations are clear: some scene elements can not be reconstructed since the geometry is limited and categoric priorities can not easily be used, and in the end the models give rise to a point cloud and a texture map, not a semantic representation which enables efficient navigation or interaction. In this project, new methods for 3D reconstruction and recognition are developed. 

Qualifications
•    Master degree in Engineering Science
•    Previously admitted to PhD studies in a related area
•    Publications in relevant international computer vision conferences 
•    Experience in computer vision and machine learning
•    Documented knowledge of machine learning, deep learning and reinforcement learning

Consideration will also be given to personal suitability, good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

Terms of employment
Fixed-term employment, four months during autumn/winter 2022-2023, start 20221201.

 


Instructions on how to apply
The application should contain a personal motivation for the application describing the suitability for the position and a description of how the applicant matches each of the listed qualifications for the position. The application should also include a list of qualifications/CV, copy of examination certificates for master or higher education, and possible other documents that the applicant wants to quote.

 

 

Type of employment Special fixed-term employment
Contract type Full time
First day of employment Snarast enligt överenskommelse
Number of positions 1
Full-time equivalent 100
City Lund
County Skåne län
Country Sweden
Reference number PA2022/3437
Contact
  • Karl Åström, +46462224548
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-2229362
  • SACO:Saco-s-rådet vid Lunds universitet, kansli@saco-s.lu.se
  • SEKO: Seko Civil, 046-2229366
Published 28.Oct.2022
Last application date 11.Nov.2022 11:59 PM CET

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