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Field
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machine learning and AI methods to develop clinical decision support systems for high-flow nasal cannula therapy. The project: Concerns around the possible negative consequences of delayed escalation
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About the project: Machine learning accelerated Inverse Design of Graphene Nanoribbons for Green Energy Supervisor: Dr Sara Sangtarash, University of Warwick Thermoelectric materials convert heat
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, the ability to analyze the full dataset collected by the experiment will be severely limited. The L2IT is a leader in developing new track reconstruction algorithms using geometric deep learning methods
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Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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environments where terrain can change abruptly. However, formally certifying these opaque learning-based components demands impractical resources, presenting critical safety assurance challenges and delaying
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the consequences of actions, and adapt reliably when the physical world changes? The project connects multimodal perception, reasoning and action with predictive learning and edge intelligence. Research directions
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Are you fascinated by how curiosity shapes learning in the classroom? Would you like to investigate how children seek information, explore and learn in real-world educational settings? If so, then
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PhD Studentship: Robust, Certified, and Scalable Federated Machine Unlearning for Privacy-Preserving AI About the Project As federated learning systems become increasingly embedded in high‑stakes
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to characterize forests and their biodiversity. The research will focus on developing multimodal learning approaches that combine complementary forest information across data sources, spatial scales, and time. A