Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of South-Eastern Norway
- CNRS
- Eindhoven University of Technology (TU/e)
- KU LEUVEN
- Norwegian University of Life Sciences (NMBU)
- The University of Newcastle
- University of Warwick
- Abertay University
- Durham University
- European XFEL
- Fondazione Bruno Kessler
- Grenoble INP - Institute of Engineering
- Inria, the French national research institute for the digital sciences
- Institut Agro Rennes-Angers
- Institute for Ophthalmic Research
- NOVA.id.FCT- Associação para a Inovação de Desenvolvimento da FCT
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- Newcastle University;
- Politecnico di Milano
- Queensland University of Technology
- REQUIMTE - Rede de Quimica e Tecnologia
- Technical University Of Denmark
- Technical University of Denmark
- Technical University of Munich
- Trinity College Dublin
- University of Basel
- University of Inland Norway
- University of Stavanger
- 19 more »
- « less
-
Field
-
the attachments exceed 30 MB in total, they must be compressed before uploading. Please note that information about you as an applicant may be disclosed publicly even if you have requested not to be included
-
Scandinavian language or in English. If the total size of the attachments exceeds 100 MB, they must be compressed before upload. Please note that information on applicants may be published even if the applicant
-
investigates a radically new paradigm for Embedded AI: enabling devices to dynamically compress and adapt neural networks directly on-device after deployment. Inspired by how humans continuously optimize
-
paid to performance across datasets, content sources, generation methods, and real-world transformations such as compression, resizing, and re-encoding. The final scientific scope will be refined
-
across datasets, content sources, generation methods, and real-world transformations such as compression, resizing, and re-encoding. The final scientific scope will be refined together with the successful
-
/C++, and experience with deep learning frameworks such as PyTorch or TensorFlow Interest in hardware aware AI, including model compression, quantization, pruning, or efficient neural architectures
-
deeper understanding is needed of how these microtissues remodel and fuse their matrices as they grow, and how this is governed by their mechanical microenvironment. As a PhD candidate, you will develop
-
Newtonian dynamics) and linear algebra (vectors and matrices). Experience working with numerical integration techniques and/or rigid body dynamics. Understanding of core networking principles (e.g. client
-
materials • Performing laboratory thermal, moisture and strength tests following relevant European or National Standards (e.g. compression, thermal conductivity, water absorption) • Investigating means
-
of ultrafast lasers, including characterization techniques as well as post-compression using Herriott multi-pass cells Development, installation and characterization of laser-driven THz sources based on organic