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Field
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Job description - Developing device-to-architecture level models of emerging nanoscale devices (spintronic, resistive, or hybrid) for in-memory and neuromorphic computing. - Exploring hardware-level
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agentic architectures for autonomous scientific reasoning and planning; • AI social scientists, including language-model-based and agent-based simulations for social science domains such as history
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, simulating, and evaluating system data, providing insights on pricing, incentive alignment, resource allocation, and multi-stakeholder interactions. Design commercial mechanisms and incentive models for LLM
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The researcher will use the ISBA land surface model developped at CNRM to study the
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BatPaC model Understanding of resource recovery technologies, supply chain analysis and upstream and downstream processes Knowledge of Aspen Plus or other chemical process simulation software. Ability
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activities: · Understanding/simulating the diffusion paths and cavitation in thermoplastic liners. · Multi-physics simulation of the diffusion process in thermoplastic orthotropic composites
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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems
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simulations (integrated modelling) can be used to better understand the dependencies obtained in scaling laws and better constrain them beyond the existing experimental space. This is the goal of the present
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financial models for capturing complex market dynamics . Assets, principal investigator Prof. Dr. Ciprian Andrei Tudor. The position is limited until 30/06/2026. Applicants with a solid practical experience
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of an Experienced Researcher with 12,50% of the regular working time is to be filled as soon as possible, for the project Non-Gaussian self-similar processes : Enhancing mathematical tools and financial models