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Field
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methods that are data-efficient, reliable, and deployment-ready. Aims Advance operator-learning architectures for transient heat transfer in complex geometries, integrating physical priors (PDE structure
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: Future study Study area: Agricultural and veterinary sciences; Architecture, building, planning and design; Arts, humanities and social sciences; Business and economics; Education; Engineering; Environment
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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. By integrating artificial intelligence (AI), multi-sensor fusion, and cognitive systems, the research will pioneer robust navigation architectures. These improvements are key to making future transport
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Excellent communication skills in English Applicants with prior experience in NLP, LLM architectures, security, privacy, safety, or robustness will be preferred. Qualification requirements PhD stipends
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of their biological counterparts. This project aims to overcome these limitations through a synergistic circuit–device co-design that jointly optimizes both circuit architectures and component properties, ensuring
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architecture of reconstituted synapses High-resolution structure determination of synaptic CAM pairs Confirmative structure-function studies in primary neurons The successful applicant will be the driver
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Electro. Responsibilities and qualifications The exponential surge in artificial intelligence (AI), internet traffic, and online services demands a revolutionary leap in devices, computing architecture, and
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characterization of advanced materials with tailored properties for cutting-edge engineering applications. We use electrochemical methods to produce advanced material architectures with high surface-area-to-volume
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for hypersonic vehicles, thermal protection systems (TPS), and propulsion environments. Exploration of carbon-carbon, UHTC composites, and multifunctional architectures engineered for harsh conditions, including