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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
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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
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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
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-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
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. Expected outcomes include: development of novel algorithms that significantly improve predictive accuracy for equipment failure; creation of scalable monitoring systems that reduce operational costs
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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
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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
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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
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model. Developing and coding the appropriate algorithms and methods that implement the novel concepts and model. Gathering experimental or observational data to test hypotheses or highlight the strength
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understanding of KB development Working with specific Robotics applications in multiple domains Proficiency with various state-of-the-art Computer Vision models Project 2. - PhD Position in Sustainable AI