Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- Cranfield University
- Newcastle University
- CNRS
- University of Amsterdam (UvA)
- Forschungszentrum Jülich
- Institute of Biochemistry and Biophysics Polish Academy of Sciences
- Norwegian University of Life Sciences (NMBU)
- Centre for Genomic Regulation
- Cranfield University;
- DAAD
- Erasmus University Rotterdam
- FEUP
- International PhD Programme (IPP) Mainz
- Linköpings universitet
- Loughborough University
- Nature Careers
- Newcastle University;
- St. Anna Children's Cancer Research Institute (St. Anna CCRI)
- St. Anna Kinderkrebsforschung e.V.
- Technical University of Denmark
- Technical University of Munich
- Universidade do Minho - ISISE
- University of Adelaide
- University of Amsterdam (UvA); Amsterdam
- University of Amsterdam (UvA); Published today
- University of Exeter;
- University of Southern Denmark
- University of Surrey
- Università di Pisa
- Vrije Universiteit Brussel
- 20 more »
- « less
-
Field
-
contribute to: Developing supervised deep learning algorithms for 3D point clouds Developing self-supervised deep learning algorithms for 3Dpoint clouds Expand for a wider variety of downstream tasks focused
-
world. We look forward to receiving your application! We are looking for a PhD student in AI and autonomous systems with a focus on Vision-Language-Action (VLA) Models to control multiple heterogenous
-
modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
-
. Expected outcomes include: development of novel algorithms that significantly improve predictive accuracy for equipment failure; creation of scalable monitoring systems that reduce operational costs
-
algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
-
-house database of experimental real-world data enabling large-scale validation of developed algorithms. Wind turbine drivetrains are critical components, and their failures can lead to significant
-
and in-house developed software to predict structures of interacting proteins and in collaboration with the Steinegger lab, developed highly efficient AI-based algorithms to compute similarity between
-
park, in a dynamic ecosystem that brings together academics and companies of all sizes. The Signal team of the i3S Laboratory (https://i3s.univ-cotedazur.fr/signal ), aims to develop advanced, innovative
-
Software. It is a collaboration between the University of Amsterdam and the Dutch Centre for Mathematics and Computer Science (CWI). QuSoft’s mission is to develop new protocols, algorithms and applications
-
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