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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 2 months ago
analysis of mechanisms, mechatronic design, and robot architecture optimization. This PhD is part of a collaborative research project with the Gepetto team at LAAS-CNRS (Toulouse). The PhD candidate will
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medicine tools for better diagnosis and treatment of breast and prostate cancer. You will work closely with computational scientists, molecular biologists and clinical researchers in a translational setting
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developing simulation flows, analysis methodologies, and predictive models that enable Design-Technology and System-Technology Co-Optimization (DTCO/STCO) studies for future systems. You will work closely with
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reaching or has exceeded its design lifetime while being exposed to harsher operational conditions than originally designed for. Fatigue, where repetitive loads initiate and propagate cracks, is a key
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-472 Is the Job related to staff position within a Research Infrastructure? No Offer Description The field of combinatorial optimization is concerned with developing generic tools that take a
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to optimize and analyze the developed sensor systems. We are looking for a highly motivated PhD candidate to strengthen our interdisciplinary research team. Be part of change Develop intelligent sensor systems
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; • mathematical modelling, development of FEM models (preferably using Ansys), and simulations, particularly in the areas of electromagnetics, power losses, etc.; evaluation, verification, and optimization
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are proud of our research endeavors, which aim at providing healthcare that is more accessible, less invasive, at a lower cost, and with optimal outcomes. We are ranked in the top 10 of NIH-funded academic
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structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We will consider techniques like flow matching, and use ideas from optimal
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-constrained devices such as wearables, smart sensors, hearables, and IoT nodes. While current deployment methodologies can optimize models before deployment, the resulting software remains static throughout