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Project Overview We are hiring highly motivated and talented Postdoctoral Associates who are interested in advancing the state of the art in resource-efficient machine learning at the Singapore-MIT
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machine learning. We focus on inductive logic programming (ILP), which learns logical rules from data. We primarily use automated reasoning techniques, such as SAT/ASP/SMT/MaxSAT solvers, to learn rules
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knowledge and advanced transfer learning techniques. The methodology incorporates fundamental radar wave propagation equations into the diffusion process, allowing for more accurate and physically consistent
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Experience in machine learning, math, and programming. LanguagesENGLISHLevelGood Additional Information Work Location(s) Number of offers available1Company/InstituteUniverCountryBrazilState
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in computer security. In particular the work will seek to deliver novel contributions that enable such systems to safely continue to operate even when they have been partially compromised and
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 2 months ago
computational mechanics and scientific machine learning. The successful candidate will work on the design of hybrid, physics-informed modeling and identification frameworks for complex dissipative material
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and machine learning. We focus on inductive logic programming (ILP), a form of inductive program synthesis which learns logical rules from data. The focus of this position is to develop ILP/program
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Postdoc position in modeling and analysis of cyber-physical systems At the Technical Faculty of IT and Design, Department of Computer Science, a full-time postdoc position in modeling and analysis
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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation
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risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include