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compliance, if applicable). Does this position have supervisory responsibilities? No Preferred Education/Experience Bachelor’s degree in Computer Science, Machine Learning, AI, Data Science, Engineering
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, and MR spectroscopic imaging using machine learning; candidates with experience in these areas are encouraged to apply. PREFERRED QUALIFICATIONS: APPLICATION PROCEDURE: Apply online at https
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. The applied practice faculty (APF) member will facilitate student learning and competency development through clinical hands- laboratory instruction (hands-on skill development, simulation) and hospital-based
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intersectionality, and inclusion of underserved populations (men, students with disabilities, LGBTQ+ students, and students from immigrant communities). Excellent verbal communication skills. Interest in learning
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(faculty, students, staff) operating machines and tools for independent research or educational purposes: -Organize and deliver instructional classes for new users of the SEAS machine shop -Instruct users in
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and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC Requirement It is the policy
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Description REALISE - Bridging Igneous Petrology and Machine Learning for Science and Society About the REALISE Doctoral Network REALISE will train 15 Doctoral Candidates at the interface of igneous petrology
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particular, we want to use machine learning/deep learning to achieve this. Currently, a basic automatic optimization module that relies on machine learning has been developed and we want to take that module
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or willingness to learn quickly. Publications, thesis work, or demonstrable projects in computer vision, multi-modal ML, digital twins or biomedical ML. Familiarity with uncertainty quantification and model
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teaching methods and strategies to engage learners, organize and plan instructional content that accommodates diverse learning styles, and devise appropriate assessment tools that monitor student learning