Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Amsterdam (UvA)
- CNRS
- Cranfield University
- Newcastle University
- DAAD
- Technical University of Denmark
- Forschungszentrum Jülich
- Institute of Biochemistry and Biophysics Polish Academy of Sciences
- Nature Careers
- Newcastle University;
- Norwegian University of Life Sciences (NMBU)
- University of Amsterdam (UvA); Amsterdam
- University of Amsterdam (UvA); Published today
- CISPA Helmholtz Center for Information Security
- Centre for Genomic Regulation
- Cranfield University;
- DTU Electro
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- Erasmus University Rotterdam
- International PhD Programme (IPP) Mainz
- KU LEUVEN
- Linköpings universitet
- Loughborough University
- Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen
- Monash University
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- Tallinn University of Technology
- Technical University Of Denmark
- The University of British Columbia (UBC)
- University of Adelaide
- University of Basel
- University of Exeter;
- University of Southern Denmark
- University of Surrey
- Università di Pisa
- Vrije Universiteit Brussel
- 29 more »
- « less
-
Field
-
for Pollinator Monitoring: Train and optimise deep learning models for pollinator detection and classification using annotated image datasets. Post-processing object tracking algorithms will be incorporated
-
vision to reduce algorithmic complexity by orders of magnitude, e.g. by tracing paths of trees and extraction from knowledge bases (KBs), as opposed to pure DL Defining specific CSK-premises (in
-
through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
-
, this research project will focus specifically on how multiple grid converter-interfaced assets should be controlled and coordinated in an inertia-less (or almost inertia-less) isolated power network, to ensure
-
aims to provide an integrated assessment of urban vegetation from multiple perspectives, including its social functions and usage requirements, the ecosystem health of green spaces linked to plant
-
new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms. What you will do You will carry out research and development in the areas
-
-tuning algorithms. What you will do You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to
-
. An optimisation tool has been developed that uses a genetic algorithm to optimise the location of BGI taking surface water flood risk reduction and the cost of different interventions into consideration. This PhD
-
. The team's main research areas are: Architectures for Autonomous Robots, Learning, Temporal Planning and Execution Control, and Algorithmic motion planning. RIS is composed of 8 permanent researchers, 4
-
are working closely with coastal communities to co-develop this platform and improve resiliency to climate events. Multiple robots will autonomously gather and transmit data real-time over a cellular network to