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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 2 hours ago
for this position, please navigate to the UT Health Careers portal at: https://wp.uthscsa.edu/careers and enter keyword 26000044. Visit our website to learn more about UT Health San Antonio and the excellent
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 2 hours ago
/careers and enter keyword 26000050. Visit our website to learn more about UT Health San Antonio and the excellent benefits we offer at https://wp.uthscsa.edu/careers/ . UT Health San Antonio is an Equal
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believe software is a systems engineering challenge rather than a coding problem. See website for details of programs: http://www.coe.neu.edu/graduate-school/multidisciplinary Responsibilities: Teach
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candidates to teach at the introductory, intermediate, and advanced levels, in both classroom and laboratory settings. We are seeking candidates who can demonstrate their experience in teaching or working with
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region. Please use the following link to learn more about YSU: https://ysu.edu/about-ysu Show more Show less Connections working at Youngstown State University More Jobs from This Employer https
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, and region. Please use the following link to learn more about YSU: https://ysu.edu/about-ysu Show more Show less Connections working at Youngstown State University More Jobs from This Employer https
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. Familiarity with frameworks such as TensorFlow and Keras, as well as libraries including Scikit-learn, NumPy, and pandas; - Experience with machine learning models such as Extreme Learning Machine (ELM
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conferimento di n. 1 incarico di ricerca scientifica di Fascia 1 presso la Sezione di Roma dell’INFN - 12 mesi Where to apply Website https://www.ac.infn.it/ Requirements Additional Information Eligibility
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based on the new data generated, incorporating key variables identified in (i), and use statistical and machine learning methodologies to ensure high predictive accuracy and robustness; iii) validation