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self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in AI deep learning model development on histology whole
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research programme on theoretical and practical aspects for reliable learning procedures for human-centred AI. The post holder provides guidance to junior members of the research group including project
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research programme on theoretical and practical aspects for reliable learning procedures for human-centred AI. The post holder provides guidance to junior members of the research group including project
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The Sehgal laboratory invites applications for a Post Doctoral Scholar position that will be based at The Ohio State University. The group is involved in several learning and memory projects, including
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learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in collaboration
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considerations from a data analysis and instrument optimisation perspective. Teach users how to operate imaging devices Understand image formation processes to design methods for optimal information retrieval from
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applying machine learning and computational methods for protein design, in close integration with experimental enzymology and biocatalysis. The tasks include: Development and application of AI and machine
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& Quant Foundations Salary Salary:$62,232.00 to Commensurate Position Details Full/Part Time Status:Full Time Percent Time:100% Position Description: Introduction: The University of Iowa’s Advanced Learning
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advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing values across different omics layers and platforms. Cross-omics data fusion and representation learning
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change via reform efforts inspired by Science Education Research and/or the Learning Sciences. The Post Doctoral Scholar will be expected to contribute to the design of qualitative (e.g., semi-structured