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infrastructures.The research of these PhD positions will be conducted as part of the EU funded SPICE (Smart Data Pipelines for the Cognitive Compute Continuum) project. Our PhD students are given the opportunity
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language processing and computer vision reveal the even greater potential of general-purpose foundation models. These models, pre-trained by SSL on diverse datasets and fine-tuned for specific tasks, offer superior
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will be conducted as part of the EU funded SPICE (Smart Data Pipelines for the Cognitive Compute Continuum) project. Our PhD students are given the opportunity to work with some of the most advanced
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. This interdisciplinary basis in computational, social, and natural sciences provides a dynamic and inspiring environment for researchers to address the grand challenges of our time. The department manages four interlinked
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computing. These include computer graphics and geometry processing, computer vision and image processing, visualization and visual analytics, augmented and virtual reality, machine learning and deep learning
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design using NMR Biologics or nanobody discovery Metabolomics This is part of your personality: We are looking for someone who: Holds a Ph.D. in natural sciences, computational sciences, or a related
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aiming to create and approve transdisciplinary knowledge in key research areas of computational sustainability. The aspirational vision of the Doctoral College is a world in which computational sciences
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Biologics or nanobody discovery Metabolomics This is part of your personality: We are looking for someone who: Holds a Ph.D. in natural sciences, computational sciences, or a related discipline Has experience
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Framework Programme? Not funded by a EU programme Reference Number 402 / 2025 / 1636 Is the Job related to staff position within a Research Infrastructure? No Offer Description Your Responsibilities
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environment with more than 70 researchers active in the fields of computer graphics, computer vision, image processing, visualization, virtual, mixed and augmented reality, and machine learning for visual