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for representing, compressing, and computing with complex physical systems. The project is carried out in close collaboration with researchers in Electrical Engineering working on emerging memory architectures and
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materials engineering, plastics and metals present complementary strengths and challenges. Metals offer strength, conductivity, and wear resistance while polymers enable complex geometries and lightweight
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The current generation of generative AI systems is still based on transformer-based Large Language Models, but they go far beyond language modelling in both complexity and capabilities. AI systems
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interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362788/post-doc-learning-interactions-… Requirements Specific Requirements PhD Degree in Physics Preferably
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materials (Goswami group) and a theory group (Wimmer group) for numerical simulations. We welcome applications from motivated and passionate experimentalists with a background in low-temperature electrical
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into different stages of optimization, both as priors and as feedback after optimization outcomes. Information This PhD project is a part of the CoRDS project – Confident Data-Driven Decision Support (https
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synthesis out of fossil-based and one time use to continuous reuse of polymeric products. Current recycling methods cannot recover high-value polymers from complex waste streams such as multilayer packaging
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practical machine learning/artificial intelligence courses and relevant project and thesis experience. You have a keen interest in AI alignment, human-AI interaction, and explainable AI, and enjoy
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qubits that build the quantum information processing machines of the future? Do you want to embed qubits in scalable systems and help bring quantum technology to real-world applications? We are seeking
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is to be the “EO innovation hub” connecting EO with a growing ecosystem of disruptive and transformative innovations such as AI, machine learning, quantum computing, edge computing, metamaterials and