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for vehicle applications; Abilities in using Finite Element modeling and analysis; Knowledge of injury biomechanics; Knowledge of Artificial Intelligent (AL) and Machine Learning (ML) techniques; and Abilities
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for this position, the following is required: PhD in data or computer science, machine learning, AI, statistics, mathematics, biophysics, bioinformatics. Additional requirements In addition to your CV and your
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Grade Level 11 Salary Range $54,080-95,056/year Type of Position Staff Position Time Status Full-Time Required Education BSN Click here for more information about equivalencies: https://hr.uky.edu
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: The participant will learn or add to skills/expertise in: Handling forest plot data, Modeling wildland fire, Modeling prescribed fire and wildfire emissions, and; Modeling tree mortality from prescribed fire and
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robust data pipelines, creating efficient machine learning models, and integrating AI capabilities into existing systems to improve efficiency, accuracy, and service quality while reducing operational
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profile and an interest in developing new AI models for high-dimensional biological data. You should have a solid foundation in areas such as machine learning, applied mathematics, statistics
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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, machine learning, or data analytics. As a proficient programmer (ideally Python), you will be curiosity-led, with exceptional communication skills, and thrive in a highly interdisciplinary environment. You
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
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/machine learning to expand the interdisciplinary faculty cluster on Translational Predictive Biology (CTPB). The selected faculty is expected to synergize with existing Translational Predictive Biology