Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Delft University of Technology (TU Delft)
- European Space Agency
- University of Twente (UT)
- Delft University of Technology (TU Delft); Delft
- Eindhoven University of Technology (TU/e)
- Utrecht University
- Delft University of Technology (TU Delft); yesterday published
- University of Amsterdam (UvA)
- University of Twente
- Leiden University
- Radboud University
- Amsterdam UMC
- Delft University of Technology (TU Delft); 3 Oct ’25 published
- Eindhoven University of Technology (TU/e); Eindhoven
- Elestor BV
- Erasmus MC (University Medical Center Rotterdam)
- Erasmus MC (University Medical Center Rotterdam); Rotterdam
- Leiden University; Published today
- Leiden University; today published
- Maastricht University (UM); Maastricht
- Radboud University Medical Center (Radboudumc); 10 Oct ’25 published
- The Netherlands Cancer Institute
- The Netherlands Cancer Institute; Amsterdam
- Tilburg University
- Tilburg University; Tilburg
- Tilburg University; 16 Oct ’25 published
- University Medical Center Utrecht (UMC Utrecht)
- University Medical Centre Groningen (UMCG)
- University of Amsterdam (UvA); Amsterdam
- University of Amsterdam (UvA); 26 Sep ’25 published
- University of Amsterdam (UvA); Published today
- University of Groningen
- University of Twente (UT); Enschede
- Utrecht University; Published yesterday
- Vrije Universiteit Amsterdam (VU)
- 25 more »
- « less
-
Field
-
learning has strong potential for computer vision, from hyperbolic image segmentation [2] to hyperbolic tree embeddings [3] and hyperbolic vision-language models [4,5]. [1] Nickel, Maximillian, and Douwe
-
physics and permeability evolution models from µCT data using machine learning and computational tools (PuMA/CHFEM/MOOSE) validated against experimental observations Bridging scales from pore-level
-
biomedical image processing. Within the scope of machine learning and computer vision, there will be freedom to suggest your own research directions, and to become acquainted with new techniques and approaches
-
geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
-
and planning status Onboard Processing of Hyperspectral Imagery: Deep Learning Advancements, Methodologies, Challenges, and Emerging Trends Onboard Processing of Hyperspectral Imagery: Deep Learning
-
, you will have experience with acquisition and processing of tomographic images, rock mechanics, machine learning and/or numerical modelling. Given the highly diverse nature of the research groups
-
/Julia) are essential. Ideally, you will have experience with acquisition and processing of tomographic images, rock mechanics, machine learning and/or numerical modelling. Given the highly diverse nature
-
(analysis/ geometry), applieddifferential geometry and machine learning;•Solid publication record in image analysis, scientific computing or machine learning.•Knowledge and practical experience in at least 3
-
learning approaches for both image analysis and experimental design Strong competencies and demonstrated commitment to FAIR data management, organization, and reproducible research practices Excellent
-
Vacancies Postdoc position on reinforcement learning on real-time image/video processing for medical robot Key takeaways In this role, you will be responsible of developing cutting-edge deep