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new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms. What you will do You will carry out research and development in the areas
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for transmission or distribution grids, synchronous generators, large loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component
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postdoctoral researcher, your responsibilities may include: Development or analysis of novel Machine Learning algorithms for engineering design applications, such as Inverse Design, Surrogate Modeling
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patients and cancer-free individuals, and will integrate these data alongside other data modalities (e.g., patient outcomes, functional genomics) to enable new clinically relevant discoveries across multiple
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 1 month ago
range of imaging and video processing fields beyond medical imaging. The Research Associate will be at the forefront of developing algorithms that are both technically robust and clinically relevant
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-tuning algorithms. What you will do You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to
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the Budget, Financial Planning & Analysis Office using multiple reporting tools including SUNY BI, Tableau, OBIEE, and Microsoft Excel and Access. This is a dynamic role that will provide the candidate
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and management of marine resources, and has a diverse research portfolio spanning multiple ecosystems, spatial scales, and levels of ecosystem organization. The Satellite Product Modeler works under
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aims to provide an integrated assessment of urban vegetation from multiple perspectives, including its social functions and usage requirements, the ecosystem health of green spaces linked to plant
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algorithm controversy game. Design Studies, 91, 101245. Hicks, B., Kitto, K., Payne, L., & Buckingham Shum, S. (2022). Thinking with causal models: A visual formalism for collaboratively crafting assumptions