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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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: Guide junior researchers and graduate students. Required Knowledge, Skills and Abilities AI/ML Expertise: Strong knowledge of advanced machine learning, deep learning, and AI techniques. Programming
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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but are not limited to modern survival analysis, high-dimensional statistical inference, AI and machine learning, deep learning and its statistical foundations, causal inference, statistical methods
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programming languages. Experience with DICOM data, medical-image registration, high-performance computing, or GPU-based computation. Familiarity with machine-learning or deep-learning methods for medical-image
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. Programming experience in Python, Matlab, and SQL. Mathematical modeling and data analysis. Machine/Deep learning (e.g. Pytorch, TensorFlow, JAX). City of Hope employees pay is based on the following criteria
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Stephen & Denise Adams Center for Parkinson's Disease at Yale School of Medicine | New Haven, Connecticut | United States | about 2 months ago
-generation AI models of gene regulation and disease progression. Our work is redefining Parkinson’s disease biology and enabling translational breakthroughs. The role Develop deep learning models across genome
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, the Postdoctoral Researcher will drive research at the intersection of health data science, multimodal AI, digital twins, computational phenotyping, and responsible AI. PhD must have been received within the last
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within the digital twin environment Developing deep learning architectures for time-series forecasting, anomaly detection, and predictive maintenance of the physical asset Designing and training Physics