Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- Nature Careers
- University of Nottingham
- University of Oslo
- Leibniz
- Maastricht University (UM)
- NTNU Norwegian University of Science and Technology
- The University of Iowa
- University of Exeter
- University of Warwick
- Cranfield University
- Ecole Centrale de Lyon
- Hasselt University
- KNAW
- Max Planck Institute for Intelligent Systems, Tübingen, Tübingen
- NTNU - Norwegian University of Science and Technology
- Norwegian University of Life Sciences (NMBU)
- Queensland University of Technology
- Sorbonne University, IMPMC-UMR 7590
- Swansea University
- Technical University of Denmark
- Technical University of Munich
- The University of Manchester;
- University of Sheffield
- University of Surrey
- University of Warwick;
- Vrije Universiteit Brussel
- Vrije Universiteit Brussel (VUB)
- Aalborg University
- Academic Europe
- CY Cergy Paris University
- ETH Zürich
- Eberhard Karls University Tübingen
- Eindhoven University of Technology (TU/e)
- Electronics and Informatics Department
- European Magnetism Association EMA
- Faculty of Science, Charles University
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- Graz University of Technology
- Grenoble INP - Institute of Engineering
- Inria, the French national research institute for the digital sciences
- Instituto Superior de Agronomia
- Jagiellonian University
- King's College London
- LEM3
- Laboratoire INSERM UMR1311 Rouen Normandie Université
- Linköping University
- Luleå tekniska universitet
- Manchester Metropolitan University;
- Medical University of Gdańsk
- Mid Sweden University
- Monash University
- Museum fuer Naturkunde, Leibniz Institute for Evolution and Biodiversity Science
- Newcastle University
- Niccolò Cusano University
- Radboud University Medical Center (Radboudumc)
- SciLifeLab
- Slovak University of Agriculture in Nitra
- Temple University
- The Open University
- The University of Manchester
- Universidade do Minho
- University of Adelaide
- University of Amsterdam (UvA)
- University of Cambridge
- University of Cambridge;
- University of Copenhagen
- University of Greenwich
- University of Leeds
- University of Lund
- University of Oxford
- University of Plymouth
- University of Southern Denmark
- University of St Andrews;
- Uppsala universitet
- VIB
- cnrs
- 68 more »
- « less
-
Field
-
Prof. David Blinder, and respectivily. Prof. Tomasz Kozacki. Traditional 3D displays are constrained by optical inconsistencies such as the vergence‑accommodation conflict, which leads to visual
-
to autonomous systems, robotics, or data-driven modelling. Demonstrable competence in at least one of the key areas related to the position (e.g., autonomous systems, sensor fusion, robot perception, drone
-
reliable transmission of demanding multi-modal data such as haptic feedback, video, and 3D sensing data. This project will develop AI-driven predictive network intelligence to anticipate delay and network
-
to create 3D models of organs and intra-operative surgical videos. The candidate will develop surgical planning and implement new technologies for its integration as VR/AR assistive platform. The research
-
are: COMSOL Multiphysics simulations of the design for optimal 2D and 3D electrode system for targeting PC Fabrication and test of the electrode system Development of variable amplitude and frequency control
-
cutting-edge research including, Generative world models, Event-based vision, Multispectral perception, 3D Gaussian Splatting and Industrial AI deployment. The team provides extensive mentoring and peer
-
- Geological 3D modelling of basement architecture - Multi-scale deformation and microstructural analysis - Targeted petrochronological studies on magmatic and deformation events - Integration with regional
-
behaviour, which requires meticulous characterisation simultaneously in 3D space and time. This essentially requires 4D imaging for a better understanding. Although traditional high-speed cameras can achieve
-
of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
-
. The tasks include developing, training, and validating deep learning–based models for event detection and vesicle tracking, and integrating these models into automated analysis and imaging workflows. The work