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of academic programs within the UCLA Joe C. Wen School of Nursing. This position requires deep familiarity with the School's unique curriculum, policies, systems (including Bruin Learn), and existing
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@emploi.beetween.com Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications Expected skills: Hold a Ph.D. in Deep Learning, Statistics, or a related field. Solid experience in
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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to contribute to the development of innovative machine learning solutions using deep learning and multimodal foundation models. Working closely with leading researchers, you will design, develop, and implement
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challenging and impactful research and development programs in healthcare informatics, bioinformatics, high performance computing and deep learning. We have a collaborative environment focusing on designing
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environment. Key research Objectives: AI Innovation (Taxonomic Identification): Developing and optimizing deep-learning architectures (e.g., YOLO) for the automated detection and classification of nocturnal
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physical models (including dispersion forces, magnetic effects, and ligand–solvent interactions), and train modern deep-learning methods to create smooth and reliable energy landscapes. A key goal is predict
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outcomes. Key Responsibilities Develop, implement, and optimise AI/ML models (artificial intelligence/classical machine learning, deep learning, computer vision, NLP, etc.) Work with structured and
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junior developers and researchers Stay current with the latest developments in Deep Learning frameworks for weather forecasting and climate science. Where to apply Website https://jobs.fbk.eu/Annunci
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latent coordinates; ii) Cross-modal alignment (e.g., canonical correlation analysis and Deep CCA) to align heterogeneous parameterizations and modalities in a shared latent space, iii) Operator learning