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have a PhD in computer science, mathematics, physics, or related fields, with a passion for programming. A desire to contribute to the development of open-source software within the context of the agreed
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voting) and sampling problems (such as graph partitions for redistricting) and to launch new research in areas connected to the work of the lab. Members of the lab publish in peer-reviewed journals in
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solutions to be implemented by others. Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation. Write and/or edit scientific content
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some overlapping measures in the individual data sets and through the use of advanced analytic tools including machine learning and graph theoretics, one can discover multiple developmental pathways in
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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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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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-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