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Viktor Larsson

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4 days ago

PhD in Machine Learning, Computer Vision, 3D Geometry, and Medical Imaging at Lund University Lund University in Sweden

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

December 31, 2026
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Country

Sweden

University

Lund University

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Keywords

Computer Science
Biomedical Engineering
Medical Imaging
Deep Learning
Mathematics
Computer Vision
Medical Science
Geometry
3d Reconstruction
Statistics
Physics
Applied Mathematic
Machine learning

About this position

Lund University is advertising multiple PhD openings in the Division of Computer Vision and Machine Learning at the Centre for Mathematical Sciences. The main themes across the posts are machine learning, computer vision, 3D geometry, 3D reconstruction, spatial AI, and medical imaging.

The featured opening, Doctoral student in Applied Mathematics with a focus on Computer Vision, is centered on learning-based methods that produce geometrically consistent outputs. The project combines geometric computer vision with modern machine learning to build accurate and reliable reconstructions and maps from visual data. Research topics include epipolar geometry, homographies, physically informed neural networks, navigation from images and video, and large-scale 3D reconstruction.

A second opening focuses on Computer Vision and Spatial AI, with work on end-to-end methods for 3D mapping, structure from motion, sensor position estimation, and audio-based geometric understanding. A third opening focuses on Machine Learning for Medical Imaging, including hybrid CNN-transformer architectures, multimodal learning, missing/noisy modality handling, and medical image analysis in collaboration with radiology and medical imaging researchers.

The positions are based at Lund University in Sweden and are part of the strategic research environment ELLIIT. The doctoral student role is full time for 4 years, with possible extension for teaching and departmental duties (up to 20%). The employment is a fixed-term doctoral studentship rather than a scholarship.

Eligibility generally requires a second-cycle degree or equivalent, plus subject-specific credits in the relevant area. Strong programming skills in Python and/or C++ are expected, and experience with PyTorch or TensorFlow is advantageous. Applicants should also have very good English, good communication skills, and the ability to work independently and collaboratively.

The application deadline for the featured opening is 2026-05-15. Applications must be submitted in English and include a CV, cover letter, degree certificates or transcripts, and any other supporting documents. The post is suitable for candidates interested in research at the intersection of applied mathematics, machine learning, computer vision, and medical imaging.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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