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recombinant minibinders for migraine-associated receptors. The project aims to advance deep learning–based molecular generation and structure-guided design for therapeutic innovation. We seek a highly motivated
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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific visionRibosome
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in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL) methods. Demonstrated proficiency in
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(but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. Experience in deep learning, machine learning and medical imaging processing Programming
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approaches to remove atmospheric particulate (e.g., PM2.5) pollution. The math-based subgroup focuses on the use of deep learning and generative AI to address critical problems for the electric grid and broad
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implement state-of-the-art data science principles into dental practice. While our primary focus is on the use of deep learning in (dental) imaging, our work expands into any type of data (e.g. tabular data
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 hour ago
mathematical and computational models of the coupled thermo-fluid dynamics of wind and surface-wave driven shelf-water polynyas in polar oceans. As magnets for biological activity, centers for deep salty water
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techniques and genomic data analysis. Background in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL
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cohorts with rich clinical data. Works on advanced modeling of post tuberculosis lung disease risk using approaches including generalized organoid models, and linear models and deep learning. Minimum
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biologically-inspired deep learning and AI models (NeuroAI). The computational models we work with include vision deep learning models (including topographical, recurrent, or developmentally inspired models