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Field
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, with a primary focus on the interface between reactor output and the ship's overall power demand. This work will be carried out on a nuclear reactor simulator, with the possibility of validating results
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will be employed and tested on actual measurement data as a benchmark. The project will involve mathematical modeling, construction of numerical methods, coding, testing, numerical simulations, and
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through simulation Utilize advanced CMOS technology nodes (28nm, 22nm, and below) Automate the design and layouts using Skill programming Develop behavioural models for circuit verification Contribute
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the selection process: U-Space Systems, programming languages (TypeScript, JavaScript, Python), and simulation. LanguagesENGLISHLevelExcellent Additional Information Benefits -Integración en un Grupo de
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient
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-driven Atomistic Simulation (DAS) group, led by Prof. Miguel Caro at the Department of Chemistry and Materials Science, Aalto University, are jointly hiring a Doctoral Researcher. In this position, you
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and its supporting infrastructure • realize on-chip pulsed DNP • design microwave pulse sequences for on-chip DNP using spin physics, numerical simulation tools, and quantum optimal control
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limited, noisy, and low-resolution measurement data? In this project, you will develop a novel physics-informed machine learning approach that integrates physical simulations of the measurement process with
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while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed
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generative AI framework that utilizes machine learning predictions and quantum chemistry simulations to design stable, synthesizable, high-performance molecules. The framework will integrate multi-objective