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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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In this position, you will join our Simulation and Data Lab for AI and Machine Learning for Remote Sensing . The lab advances interdisciplinary research and operational services by combining
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quantitative field. Good scientific programming skills, particularly in Python, are required. Experience with atmospheric dynamics, numerical modelling, machine learning, or large meteorological datasets would
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provide GPU computing for machine learning on Aalto's Triton high-performance computing cluster, alongside industry-standard circuit simulation tools (Cadence, Synopsys, etc.) on our own computing cluster
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of expertise Most candidates will have experience with data science or machine learning, but ultimately, we’re more interested in how you think and learn than what you currently know. PhD or other research
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on machine learning and networks, release the code in open access and actively participate in the international interpretability community. Where to apply Website https://seuelectronica.upc.edu/en/procedures
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machine learning, computer vision, robotics, efficient inference or embodied AI, prioritising practical, reliable systems. Durham offers strong facilities: Bede HPC (128 GPU), GPU cluster (90+ GPU), LiDAR
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robot learning and edge deployment. Closing date: 15 August Overview Robotics is entering a new phase where foundation models connect perception, language and action. Vision-language-action models, robot
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machine-learning strategies for multimodal representation learning and for the integration of the complex biological datasets generated within the consortium. Duration and start date: 48 months, full-time
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of dynamic radar scenes. The project combines methodological machine learning research with experiments on real automotive sensor data. You will have access to research vehicles and advanced radar prototypes