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in research at the interface between geometry, analysis, computation, and machine learning. Postdoctoral positions Applicants for postdoctoral positions are expected to have a strong background in
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to mentoring students and postdoctoral researchers in a collaborative and inclusive environment that promotes scientific curiosity, technical rigor, and professional growth is also expected. Teaching
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insurance, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records
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simulation, artificial intelligence and machine learning-guided design of cyclic peptide aptamers based on structural characterisation of alpha-conotoxin/nAChR interactions’ working with Professor Andrew
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-driven methodologies, including machine learning and AI-based experimental design, for accelerated formulation and evaluation of battery materials. This enables faster iteration cycles, improved
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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California State University, Long Beach | Long Beach, California | United States | about 2 months ago
undergraduate and/or graduate level courses in computer engineering, computer science, software engineering, or any related areas At least one year of postdoctoral or equivalent research experience in software
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/machine learning (AI/ML) being a major focus. Many of the laboratory's interests center around the identification of small molecules using mass spectrometry data, and the use of language models to predict
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-accredited doctoral internship and multidisciplinary training program including practicum and postdoctoral fellows. The center is accredited by the International Accreditation of Counseling Services (IACS) and
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hardware Experience with atomic layer deposition and process development Experience with thin film and materials characterization Strong background in computational materials science and machine learning