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Field
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and molecular simulation experience. A solid background in simulation algorithms and experience in advanced scientific computing are highly desired, as is a solid background in chemistry or biophysics
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field (e.g. statistics, computer science, or quantitative biology). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming
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: Artificial Intelligence, including but not limited to Machine Learning, Responsible AI, and Computer Vision; Theoretical Computer Science, including Algorithms, Algorithmic Fairness, Game Theory, and Learning
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1,000 full-time instructional faculty. General Information: The JMU Optimization & Algorithmic Theory (OAT) Lab is looking for up to four (4) student research assistants (RAs) to join our team! The OAT
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environmental engineering (candidate status) and a demonstrated record as a lead author on publication(s) using machine learning algorithms to forecast water quality. Fluency with open source coding languages (R
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or hands-on lab environments. Having taken Data structures, algorithms, Theory of computation courses with a good grade Modes of Work Hybrid The work requirements allow both onsite and offsite work and an
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. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software packages for data
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modeling, computational complexity, or algorithm analysis. We are especially interested in candidates experienced in teaching with computational tools who can work alongside current faculty to incorporate
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networks, transformers, and diffusion models. Proven experience building AI solutions using classical ML algorithms such as decision trees, gradient boosting machines, and shallow neural networks
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 9 days ago
++, taking advantage of Spark, Hadoop, and other tool stacks as appropriate. * Developing computational and algorithmic approaches to understanding the neurobiological mechanism of neurodisorders. * Interact