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field such as computer science, bioinformatics, mathematics, computational life sciences, or related. Profound knowledge in machine learning, preferably deep learning for image data. Experience in
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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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Benefits , Postdoctoral Landing & Postdoctoral Fellow Stipend (Download PDF reader) sites to learn more. The salary for this role is $78,000.00 per annum. The salary range or hourly rate listed is a
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survival data using longitudinal features, and (6) machine learning and deep learning for analyzing time-to-event outcomes, or (7) radiomics and medical imaging analysis. Required Qualifications: We seek
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participation in proposal writing. Her/his technical proficiency should encompass isotope geochemistry, hydrogeology, and numerical modeling. A deep understanding of serpentinization processes, including water
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materials to jonc101@stanford.edu (link sends e-mail) Does this position pay above the required minimum?: Yes. The expected base pay range for this position is listed in Pay Range field. The pay offered
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: Information Science / education Appl Deadline: (posted 2025/01/28, listed until 2025/07/28) Position Description: Apply Today is the last day you can apply for this position; no new applications will be
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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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and model vadose fluid transport in the deep vadose zone (10s to >100 m depth) in California's Central Valley. The research will focus on the use of geophysical tools to parameterize and validate