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related to staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 21 days ago
for automated content generation while maintaining pedagogical constraints, deploy targeted generative guidance aligned with established learning theories, and create compact student models for next-generation
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mathematics, Earth science, or a related discipline Skills in numerical modelling, programming, and handling large datasets Prior experience in machine learning is desirable Interest in nonlinear dynamics and
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. Into the second year, the project moves toward methodology refinement and Machine Learning integration. The student will execute a more ambitious cycle with a complex alloy system and integrate machine learning
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Institute on advanced machine learning projects that use historical behavioral data to predict outcomes and inform strategies to improve engagement and solicitation effectiveness. Additionally, the Lead Data
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for collaboration. You will also have the opportunity to develop your own research project aligned to the interests of the MND group. This could include new machine learning models or exploring a particular aspect of
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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fluorescence microscopy (SMLM, SIM), integrating physical-mathematical models, machine learning, and compressed sensing for accurate and efficient reconstructions. Applicants must submit a project implementing
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including antenna and/or microwave engineering * programming skills and working knowledge of Matlab programming environment * knowledge of mathematical modelling, machine learning and artificial intelligence
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manufacturing principles. Experience with machine learning methods and integration into hybrid modelling systems Demonstrated ability to clearly communicate research concepts and results in high-quality journal