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inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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point-based PhorEau projections using a machine-learning model predicting tree species richness as a function of spatially explicit abiotic and biotic covariates, including satellite-derived data
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federated learning, AI security and privacy, quantum machine learning (QML), robotics, and/or AI-driven discovery in science and engineering (e.g., genomics, bioinformatics, drug discovery, infectious disease
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Energy Storage! Fully funded 4-year PhD Studentship in Chemistry - Machine Learning-Accelerated Quantum Chemical Modelling of Molecular Junctions and Surface Catalytic Reactions PhD Studentship: Taking
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device health status through condition monitoring. AI techniques such as machine learning will be used to optimise gate driver performance and to map gate drive signal attributes to power device health
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machine-learning scripts that feed into these pipelines. You execute and monitor these scripts, then integrate their output into project datasets. Throughout this work, you maintain clear documentation
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urban design with microclimate simulations and measurements, GIS and Digital Twin technologies, and machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based
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expertise in machine learning, soil microbiomes, microbial 3D printing and biophysics, our team has access to a broad spectrum of techniques and practical know-how. This is therefore an exciting opportunity
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Areas: computer science; applied math; artificial intelligence; machine learning; statistics; engineering Appl Deadline: 2026/02/06 11:59PM (listed until 2026/06/19) Fellowship Description: Apply