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This exciting opportunity is based within the Composites Research Group at Faculty of Engineering which conducts cutting edge research in advanced manufacturing of high-performance composites Vision
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Institut de Recherche pour le Développement (IRD) | Montpellier, Languedoc Roussillon | France | 9 days ago
Optional Skills / Knowledge Expertise in statistics Expertise in high-performance and parallel computing Expertise in neural networks Personal Qualities Intellectual curiosity Autonomy Adaptability Rigor
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artificial intelligence and genomics. The institute also has high-performance computing infrastructure (hundreds of CPU cores, over 100 TB of storage) essential for processing the massive single-cell
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biofeedback in people with CLBP to alter the way their muscles contract and explore the impact this has on pain symptoms and task performance. This project will integrate experimental research with the patient
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DTU Tenure Track Researcher in Experimental High Pressure Phase Behavior for CO2 Storage and Othe...
to the development and improvement of experimental methods and measurement techniques in this field. High-pressure phase behavior and thermophysical properties are essential for the reliable design and safe operation
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to enable quantitative, high-resolution, time-lapse monitoring of soil properties and will be implemented using high-performance parallel computing. This PhD position offers the opportunity to work at the
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scalable workflows that integrate physics‑based modeling with data‑driven approaches, while efficiently utilizing national and local high‑performance computing (HPC) resources. Essential Function Yes
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to support model development. Accordingly, you will gain access to the high-performance computing (HPC) facilities at QUT.
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‑stationary atmospheric conditions involving shear, veer, yaw misalignment, and wake interactions. High‑fidelity CFD methods (RANS/LES) can capture these effects but are too computationally expensive
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scientific datasets. Integrate cloud platforms, high-performance computing resources, and collaborate with infrastructure teams employing MLOps tools for scalable experimentation and deployment. Document and