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Field
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conducts independent and collaborative research activities focused on advancing scientific knowledge and improving clinical outcomes. The successful candidate will contribute to the design, implementation
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of SATURNA, namely Language Models for RNA sequences, Graph representation learning and generative models, Knowledge-Augmented RNA modeling, Computational RNA biology and Experimental stem cell biology and RNA
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the field of Automated Reasoning for Quantum Knowledge. Position You will assist in ongoing research projects in classical representation and reasoning of quantum knowledge You will help coordinate project
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different forms of representation. Postdoctoral Researcher in Science Education Our goal: To better understand how students interpret, evaluate, and represent scientific evidence, and to improve instructional
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they compare evidence, calibrate uncertainty, justify claims, and move between different forms of representation. Postdoctoral Researcher in Science Education Our goal: To better understand how students
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the cognitive neuroscience of language, multilingualism and spatial cognition, including entorhinal cortex based spatial grids and cognitive maps. The ideal candidate holds a degree in Biomedical Engineering
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independently and collaborate within a team structure Knowledge of plant breeding and selection theory Preferred Qualifications: Experience with herbicide tolerance and selection in breeding programs Supervisory
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, the person will perform professional-level work in scientific research, utilizing advanced skills and knowledge to execute the following tasks: plan field and laboratory experiments based on the season and
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Science Foundation (NSF) grant entitled “RTG: Combinatorics, Geometry, Representation Theory, and Topology” at the University of Oregon. Applicants should be in research areas connected to one of these four
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understanding and representation learning; Self-supervised and data-efficient learning; Transfer learning and knowledge reuse across tasks; Structured and compositional learning; Vision-language and multimodal