Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- NTNU Norwegian University of Science and Technology
- Hasselt University
- CNRS
- Eindhoven University of Technology (TU/e)
- European Synchrotron Radiation Facility
- GFZ Helmholtz-Zentrum für Geoforschung
- Inria, the French national research institute for the digital sciences
- Leiden University
- NTNU - Norwegian University of Science and Technology
- Tallinn University of Technology
-
Field
-
to analytical applications of design standards) is highly valued, as is a proactive commitment to mastering these tools. An interest in computer vision, visual computing, 3D visualization, or related domains
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09928 Requirements Skills/Qualifications Profile: - The candidate is completing a Master's or engineering’s degree in Computer Vision, Electrical
-
Sklodowska-Curie Doctoral Network linking 21 academic, cultural, and industrial partners to develop advanced nondestructive evaluation and data-driven digital tools for paintings and 3D artworks (https
-
, voids, delamination, corrosion, and internal structural discontinuities. The PhD candidate will investigate Vision Language Models (VLMs), Multi-modal AI solutions, and 3D scene reasoning approaches
-
tracking and mapping, light fields, extended reality (XR) technologies, sim-to-real, synthetic data generation, and advanced computer vision and machine learning techniques. In addition, the group works on
-
creation of tender documents, specifications, and requirement structures. 2D and 3D spatial reasoning, including general arrangement exploration, layout optimization, and constraint-aware geometry generation
-
Grenoble, France. Through its innovative engineering, pioneering scientific vision and a strong commitment from its 700 staff members, the ESRF is recognised as one of the top research facilities worldwide
-
to research solutions and to transfer our knowledge to society. We are doing this according to our vision: “Taking the pulse of our Earth to safeguard a habitable planet”. For section 2.2 Geophysical Imaging
-
vision imaging technologies and machine learning methods to estimate physiological parameters (eat-readiness, shelf-life) of fruits at industrial sorting speeds. The work will include creating an accurate
-
Participate in the research group “Engineering Geology and Rock Mechanics” and FME RenewHydro (https://www.ntnu.edu/renewhydro ) Participate in international activities such as conferences Contribution in