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computationally efficient numerical structural models. To support the condition (state) assessment, the project will also explore the use of advanced estimators (e.g., Kalman Filter) or Machine Learning models
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methods and solutions and in architectures and systems that support the development of such systems Publish research results and present them at international conferences Contribute to reports and research
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experiments, and parametric investigations. The modelling component will be based, as much as possible, on semi-analytical thermo-mechanical formulations. This is to facilitate calculation accuracy, numerical
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approach for OFR, building further on existing methods; (2) quantify the value of OFR in Luxembourg ; (3) quantify the impact of forest disturbances on the OFR supply and value; (4) estimate the supply and
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and Topology; Analysis; Geometry; Numerical Analysis and Optimization; Probability and Statistics). (c) Production and edition of scientific papers and progress reports on his/her research work. (d
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, significantly enhancing the visibility of products, resources, materials, and activities. The PhD candidate will develop methods and processes that utilize such technologies to plan and coordinate manufacturing
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numerical modelling skills (e.g. Python, MATLAB, CFD codes) Personal characteristics Flexible and dependable Collaborative and independent Innovative and open minded Strong analytical skills Emphasis will be
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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Your Job: Digital methods for inverse materials design are essential to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 2 months ago
induces reduced footprints for processors and less space for the battery. On the audio processing latency front (iii), DNN inference is notoriously slower for real-time audio DSP than “traditional” methods