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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse
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in question. Although the current state-of-the-art neural MT (NMT) models are capable of producing high-quality translations for many languages, they are still not on par when it comes to translating
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courses in one or more areas such as digital painting and drawing, character design and animation, virtual environment design, interactive media, 3D modelling and animation, digital assets construction
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testing and optimisation of various decarbonisation scenarios. For more information please visit the TransiT website https://transit.ac.uk/. We are seeking a proposal for a project contributing to Digital
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in workplaces, integrating real-time data and models compliant with EN 62305-1. Where to apply Website https://careers.polito.it/ Requirements Additional Information Eligibility criteria To apply
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researchers from the modelling and experimental teams to link data and model components Your Profile: You are enrolled as a student at a German university You study Biology or a related field in natural
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Person Registry (Person Dimension). Will also design, develop, and validate workforce data models that integrate traditional and AI-augmented approaches. Leveraging dimensional modeling principles (Kimball
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the project: Develop, train, and optimise deep learning models for wildlife species identification, classification, and segmentation using real-world datasets. Design and implement software modules to integrate
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA CIVILE, CHIMICA, AMBIENTALE E DEI MATERIALI | Italy | about 1 month ago
. Structural optimization and numerical modeling. Where to apply Website http://www.unibo.it Requirements Additional Information Eligibility criteria to apply for research grants fill out the form available
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protein structural insight with hands‑on ML development: adapting and applying state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational