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learning algorithm to analyze how experimental parameters ( 3D printing and electrospinning) affect the design. At least 3 semesters of FIU work experience or related experience outside the University with
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engine. Algorithm Development: Contribute to designing, prototyping, and testing algorithmic models for personalized content recommendations. System Evaluation: Support the evaluation of the recommendation
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 2 months ago
. Duties/Responsibilities Analysis (50%) Develop machine learning algorithms to analyze ground magnetic field perturbations Analyze the results using machine learning interpretability techniques
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Prof. Mingzhou Jin (jin@utk.edu ). Application Process This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can
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thousands of visiting researchers each year. To learn more about ORNL visit https://www.ornl.gov . For questions, please contact Prof. Hongyu Nick Zhou (hzhou8@utk.edu ) or Prof. Mingzhou Jin (jin@utk.edu
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Professional References including names, addresses, and telephone numbers A portfolio of design works For questions, please contact Prof. Mingzhou Jin (jin@utk.edu ) or Prof. Marshall Prado (marshall.prado
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for engineering-driven AI innovation. Ideal candidates will have: (1) A PhD in Management Science and Engineering, Computer Science, or a related discipline, with a focus on AI/ML theory, algorithms
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Position overview Position title: Dean, Division of Graduate Education and Postdoctoral Affairs. The successful candidate should hold an underlying prof-AY title. Salary range: $300k-$350k Review
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://www.ornl.gov . For questions, please contact Prof. Niki Labbé (nlabbe@utk.edu) or Prof. Jon Shefner (jshefner@utk.edu). Application Process This institution is using Interfolio's Faculty Search to conduct
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collection, and data analysis. Work activities may include the following. • Developing analysis tools to extract physical meaning from in-situ process data. • Developing machine learning algorithms to drive