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Doctoral Researchers (PhD students) to work on deep learning methodologies for machine and robot perception. These positions are funded by the Horizon Europe project OPERA (Open Perception, Learning, and
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intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in
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reconfigurable RF hardware for CAP-MIMO systems and contributing to machine learning-enhanced ISAC methods development through EM-informed modelling and hardware design. This is a unique opportunity to build
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for a full-time, on-site PhD position in machine learning, forecasting and time series analysis. Reykjavik University, Department of Engineering. Duration: 3 years. Start date: Negotiable. Reykjavik
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project), create a unique opportunity to apply machine learning and neural network methodologies, in conjunction with simplified ice sheet models, to advance understanding of ice sheet basal processes and
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environment where machine learning meets real-world scientific impact. What You’ll Do: Conduct cutting-edge research at the intersection of AI and science Develop large-scale deep learning models for scientific
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research will be conducted within the VLAIO ICON NEXT-WIND project, which aims to develop next-generation forecasting methods combining machine learning weather prediction models with renewable energy
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solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Independently
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in
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. Position: Job Summary: The Interactive Graphics & Video Editor (3D Senior Artist) sought to design, create, and animate 3D and interactive learning assets, illustrated characters, and environment assets