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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
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, the fusion community has started to develop fast surrogate models based on Machine Learning / AI models to speed up significantly the employed tools. Such tools have demonstrated to be generally applicable and
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prestigious ERC Consolidator Grant in a great interdisciplinary institute in Amsterdam. Join us! Are you passionate about machine learning, natural language processing and generative AI? We are seeking a
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models that provide evidence-based reasoning for mission-critical decisions. Explainable AI for mission-critical decision support: design interpretable machine learning architectures capable of offering
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longitudinal datasets, you will model how economic, educational, and political drivers have shaped the visibility of women artists over centuries. You will not only analyze these patterns but also collaborate
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and digitizing archival data, strong knowledge of causal inference methods, good command of R and Python. Knowledge of machine learning methods is an asset. Strong command of English; command of either
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outcomes under different market design scenarios. The research will combine machine learning, stochastic optimization, and agent-based modelling with behavioural experiments. Case studies from emerging
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://www.academictransfer.com/en/jobs/357341/postdoc-position-on-federatedco… Requirements Specific Requirements We are looking for a researcher who sits at the intersection of Pervasive/Mobile Computing and Machine Learning
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leverage large-scale AI models to: integrate heterogeneous EO data sources, such as satellite, aerial and in-situ data, across spatial and temporal scales; enable zero-shot or few-shot learning for rapid
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-generated scenarios or machine learning-driven attack/defense strategies; Experience in developing comprehensive security assessments, producing technical reports, and contributing to toolkit documentation