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architectures [5] and Neural ODEs [2], creating a cohesive end-to-end hydrological model. Transformers will be utilized to pre-process and analyse the raw input data, capturing essential spatial and temporal
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This PhD project aims to develop and apply innovative photogrammetry-based analytical tools to enhance the spatial and structural characterisation of pharmaceutically relevant materials, with a
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processes that produce energy and raw materials. The Department of Reactive Transport is looking for a PhD Student (f/m/d) Tomography of desorption reactions: positron emission tomography for quantifying
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effective for designing and optimizing applications for reconfigurable/spatial computing architectures (HW/SW co-design)- Extend or build simulation or modeling frameworks to support systematic exploration
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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The National Industry PhD Program is an Australian Government initiative to enhance workforce mobility among graduate researchers, and to promote knowledge transfer between academia and industries
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Ecole Polytechnique Federale de Lausanne, Unsteady Flow Diagnostics Laboratory Position ID: Ecole Polytechnique Federale de Lausanne-Unsteady Flow Diagnostics Laboratory-PHD [#30284] Position Title
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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace
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garments into recycle, reuse, and manual-review streams; this PhD project tackles the core challenge of designing and optimizing a high-throughput hyperspectral imaging system, fused with complementary