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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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Grade Level 44 Salary Range $21.06-33.69/hour Type of Position Staff Position Time Status Full-Time Required Education AS Click here for more information about equivalencies: https://hr.uky.edu/employment
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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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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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, 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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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
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at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally
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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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groups and individuals and through mass media. Ability to use the computer for program delivery and management. Ability to visit clientele at sites throughout the county. Ability to plan and teach
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individuals and through mass media. Ability to use the computer for program delivery and management. Ability to visit clientele at sites throughout the county. Ability to plan and teach educational programs