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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours 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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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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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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. 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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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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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Sete, Languedoc Roussillon | France | about 18 hours ago
influence on lagoon ecology. Deconvolving the effects linked to trophic variables from those linked to climate change is also a scientific challenge, for which AI techniques (algorithms, machine learning
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knowledge of and/or experience with validation of prediction models (regression or supervised machine learning), health technology assessment, decision curve analysis, and/or value-of-information analysis