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Field
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them in this task. In this course, we will introduce the foundation concepts of data visualization such as proper use of different graphs. The course will cover the complete life-cycle of data
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at an international level developing deep learning, vision transformers, graph neural networks, foundation models, or related methodologies for integrating diverse imaging data with clinical, laboratory, and genomic
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Statistical Software : Proficiently use R and RStudio to perform data analysis, create scientific graphs, and interpret results. Develop Problem-Solving Skills : Demonstrate the ability to tackle real-world
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Description This PhD project bridges computational neuroscience and machine learning to study the mechanisms of active forgetting—or unlearning—through the lens of both biological and artificial systems
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-3 three years in the AI/ML arena, is required for consideration. An overall combination of equivalent experience may be considered. Masters and PhD degree holders in the same fields of study are also
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of aligned experience, with the last 2-3 three years in the AI/ML arena, is required for consideration An overall combination of equivalent experience may be considered. Masters and PhD degree holders in
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Situated in Stanford's highly dynamic research environment the Curtis Laboratory (http://med.stanford.edu/curtislab.html ), led by Christina Curtis, PhD, is seeking a bioinformatician/Research Data Analyst 1
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replacement) project on Limits of Symmetric Computation. The position would suit a candidate seeking to obtain a PhD at the Department. The project seeks to investigate lower bounds on symmetric computation in
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robots. They will be working with a team composed of PhD students, Research Assistants and Postdocs that is developing novel multi-robot architectures for practical, real-world settings. Current solutions
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related field Sound knowledge in the field of artificial intelligence and machine learning Ideally experience with knowledge graphs, semantic search, graph neural networks (GNNs), explainability