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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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, behavioral economics, and machine learning, to help policymakers identify and generate evidence on innovative approaches and policy solutions to their most pressing environmental and energy challenges. Job
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. · Experience working in a community college setting. · Experience with predictive modeling and machine learning techniques. · Supervisory experience Operation of a State Vehicle Yes Supervises Employees
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initiatives is highly desirable. Experience with computational tools (e.g., CFD, FEA, system-level modeling) and/or experimental platforms for energy systems is expected. Position # 2 - Machine Learning and AI
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project, you will develop machine learning models that learn from high-throughput experimental datasets to uncover structure–property relationships and guide the selection of new experiments. The datasets
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of environmental hydraulics. We seek someone who is “hands-on” and would be excited to contribute to physical model design and construction. The position also carries responsibility for assisting with
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these challenges by: Developing predictive workload, lead-time estimation, material planning models to capture the high variability in HMLV environments using hybrid AI (combining machine learning, feature-based
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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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ADC performance against acute myeloid leukaemia (AML). Laboratory experiments and machine learning models will be implemented to achieve the following aims: Develop a random forest regression model
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, funded by a Leverhulme Trust Research Leadership Award held by Dr Alessio Spurio Mancini. ECLIPSE's goal is to develop next-generation inference frameworks that combine machine learning with rigorous