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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning
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teaching duties. Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information Systems, or a related field, and sufficiently demonstrate abilities to conduct high-quality
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teaching duties. Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information Systems, or a related field, and sufficiently demonstrate abilities to conduct high-quality
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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performing theoretical DFT calculations for solid-state systems and lattice dynamics calculations applying machine learning techniques to predict the solubility of pharmaceutical cocrystals supervising and
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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Research Infrastructure? No Offer Description Based at Australian Institute Machine Learning (AMIL), City East Campus 2 x Full-time, 2-year fixed term contracts Salary Range: $114,917 - $135,932 per annum
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thesis is not pre-defined and should be defined by the candidate over the course of the first year. The domain of the PhD thesis must be machine learning and either control theory, path planning, or multi
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. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and multi-omics data. Additional responsibilities include mentoring students, collaborating with faculty
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application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through scaling model sizes, training budgets