426 algorithm-development-"Multiple"-"University-of-California,-Santa-Cruz" positions
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Details Position Description The University of Washington, Department of Radiology, has openings for multiple postdoctoral scholar positions. The research projects will focus on advancing rapid
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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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employment This is a 7-month position from October 1st, 2025, or as soon as possible. Job description You will participate in the ongoing development of an algorithm platform for digital shadows and twins
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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model performance across multiple development iterations. This hands-on experience will provide valuable insight into the application of AI and geospatial technologies in environmental research. What
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energy, personalized medicine and climate science and we need your help to develop tools and workflows to drive exploitation of this world leading resource. You will also play a key role in fostering a
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of pediatric cancer patients and discover the impact of therapeutic exposure on development of secondary neoplasms in adult survivors. Position Responsibilities: Evaluate bulk-tumor deconvolution algorithms
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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, which has multiple test machines with GPUs and AI accelerators. The algorithms used can be bound by the available compute power or memory bandwidth in different parts of the program. This information will
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accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing