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Field
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software, computing or triggers for the ATLAS experiment would be highly desirable, as would experience with deep learning and concurrent programming The post will work in the first instance the High Energy
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/Administrative Internal Number: 7319007 University of California Irvine Postdoctoral Researcher/Lab Scientist Deep Phenotyping Position overview Salary range: The salary range for this position is $66,737-$82,836
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candidates will have experience in artificial intelligence, deep learning or decision support applied to RF sensing, wireless communications and signal processing. A strong background in multimodal data
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Science / Engineering, Electronic Engineering or a closely related discipline, with a good track record of original research publications. The successful candidates will have experience in artificial intelligence, deep
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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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have skills in eukaryotic cell biology, electron microscopy, and bioimage analysis. You have a basic knowledge in integrative structural biology, and in AI / deep learning approaches and/or sub-tomogram
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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
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-facing web GIS dashboard. Investigate the forest, landscape, and climate conditions that drive storm susceptibility, using major windstorms as natural experiments and interpretable machine-/deep-learning
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strong background in image processing and analysis, including deep learning experience with correlative imaging workflows and 2D/3D registration techniques strong programming skills in Python and/or C/C
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the eBird project, one of the largest sources of avian biodiversity information in the world. The eBird team is a collaborative and innovative group that includes staff with deep expertise in bioinformatics