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Field
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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learning techniques, and on the development of integrated motion-corrected analysis of positron emission tomography (PET)/computed tomography (CT) angiography imaging. As a Project Scientist, you will work
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imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets
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adaptive reflexes that maintain homeostasis. How its signals are encoded, transmitted and routed to distinct brain circuits remains a fundamental open question. We are seeking an outstanding Postdoctoral
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attribution, representation analysis, causal probing, and mechanistic circuit analysis. The postholder will also develop predictive models using modern deep learning frameworks (e.g., PyTorch) and evaluate them
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techniques, protocols and algorithms, and data analysis and interpretation including image reconstruction and deep learning techniques. Participates in publications, scientific abstracts, and presentations as
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geometry, temporal generalization). Computational measures of visual information (e.g., image statistics/compressibility proxies, deep network features, object/scene representations). Position Summary
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research efforts in the areas of amorphous materials and physics, as well as AI-assisted new materials design, the center is committed to integrating computational simulation, data science, and deep learning
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imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets
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in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence, collaboration, integrity, diversity and