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on quantitative phenotyping via generative modelling of quantitative MRI data. This exciting PhD position combines advanced machine learning with medical imaging physics to develop next-generation tools
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modalities Experience with signal enhancement, machine learning, or data-driven imaging analysis Track record of publications in high-impact scientific journals, conferences or patents. Experience contributing
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early detection is a need that needs to be addressed using advanced sensors. The candidate will apply machine learning and IA methods to anticipate the evolution of the discharges. This project aims
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Grade Level 41 Salary Range $15.83-25.30/hour Type of Position Staff Position Time Status Full-Time Required Education HS Click here for more information about equivalencies: https://hr.uky.edu/employment
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research background in or research experience with one or more of the following topics: Natural language processing & language modeling Machine learning & representation learning Interpretability and
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of applying molecular models at process scales, the project combines efficient mathematical concepts like automatic differentiation with backpropagation – the same concept that powers machine learning and
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mathematics, Earth science, or a related discipline Skills in numerical modelling, programming, and handling large datasets Prior experience in machine learning is desirable Interest in nonlinear dynamics and
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, or machine learning models). Experience with high-performance computing and version control (e.g., GitHub). History of large-scale project implementation work in an international setting (e.g, population
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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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benchmarking of deep learning sequence-to-sequence architectures Implementation of new machine-learning layers and model components Application of tools for genome analysis and molecular evolution The position