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of ORCRIST: Optimized Ray-tracing for Cloud-Radiation Interaction Simulations in 3D using GPUs and Machine Learning, funded by the NWO Open Technology Programme. Sunlight and heat radiation move
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between predictive performance, computational efficiency and scalability, using high-performance and cloud computing environments. Depending on the agreed research direction, you may also explore hybrid
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for revolutionary industry applications. In the near-term, the access to quantum processors is provided through shared environment via cloud systems. In this model, many users access the same quantum processor
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to teach robots to understand forest well enough to navigate and move through them in real time, using machine learning on LiDAR point clouds and camera imagery for real-time understanding of the forest
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with support from biostatisticians within the group. The bioinformatic work will be performed using high performance cloud computing solutions. This project offers the opportunity to utilise emerging
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are still present. This PhD research aims to develop new and efficient AI-based solutions for processing LiDAR data (2D/raster and 3D/point clouds) and improve the detection of sub-canopy archaeological
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Integrated optics is currently experiencing unprecedented growth, driven largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing
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, experience working with large-scale geospatial datasets and high-performance or cloud computing, and demonstrated expertise in advanced machine learning. Experience leading research projects, managing budgets
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into insight). To tackle this, the research blends ideas from knowledge graphs, stream processing, database theory, logic, edge and cloud computing, and Artificial Intelligence into a single coherent framework
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-constrained Physical AI by dynamically distributing and adapting AI workloads across embedded devices, the edge, and the cloud, while jointly orchestrating communication, computation, and sensing under strict