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— systems. It targets pioneering an architecture optimized for bilateral sensor processing. By fusing multiple data streams, VEST-CHIP aims to improve health tracking accuracy and unlock capabilities such as
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ultramafic rock systems. The position is associated with ongoing research aimed at advancing understanding of mineral fluid interaction processes and their impact on subsurface architecture and petrophysical
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large organization preferably the financial sector or the health sector. Particularly, the research in the position is devoted to the role of IT architecture in enabling digital platforms and digital
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. Typical research questions could be: How can tacit systems-architectural knowledge be captured and shared between humans and with machines? How to effectively collaborate on an architectural level with AI
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hand and body configurations, surfaces, graphs and in permutations of inputs. Prominent architectures - including Graph Neural Networks (GNNs) and Convolutional Neural Networks (CNNs) - can be viewed as
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be analysed onshore for various physical and chemical characteristics to help constrain the 3D stratigraphic architecture and compositional variability of the deposit. The datasets will be used
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observing system can help to build data-driven ML forecasts. The tasks of the PhD fellow will be to design the architecture and train a generative emulator of the coupled ice-ocean-biogeochemical model
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optimizing compilers, the classical and quantum fragments are separated in efficient implementations adapted to the changing QPUs and GPUs architectures. The candidate will work at the intersection
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candidate will work with open available datasets obtained in rodents and unique datasets of neural activity. Your primary focus will be to design new learning frameworks and neural network architectures
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. Particularly, the research in the position is devoted to the role of IT architecture in enabling digital platforms and digital ecosystems. This includes but is not limited to various strategies chosen by