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of isolated clones using biochemical, biophysical and imaging methods. Engineering of protein tools using chemical or genetic methods for use in a cellular environment. Validation of tools in cellular models
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intelligent decisions. In particular, when low latency is critical, these models are deployed directly on devices at the edge, close to the equipment itself — a necessary condition for smarter, faster
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chemistry, materials science or equivalent having carried out research in an experimental field related to the thesis. Core competencies: crystal growth thermodynamic modeling chemical and physical
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), Biochemistry (production and purification of protein complexes), Structural biology (cryo-electron microscopy and image analysis). The final goal is to build a mechanistic model of substrate recruitment by
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tools • Modeling of devices with the finite element method • Micro-nano fabrication in the IEMN's clean room • Physical / Electrical characterization of devices • Participation in the ANTARES project
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emerging models by collaboratively exploring various computation models leveraging physical devices properties. This PhD work will focus on FPGA devices in order to build an accelerated spiking neural
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modeling. Each PhD will lead to a double degree awarded by two partner universities, preparing graduates to become leaders in Europe’s energy transition. DC7 PhD Position "Uncertainty Quantification
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will equip 15 PhD researchers with cutting-edge expertise in combustion science, chemical kinetics, fluid dynamics, and digital modeling, preparing them to revolutionize industrial energy systems and
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utilization. DESIRE will equip 15 PhD researchers with cutting-edge expertise in combustion science, chemical kinetics, fluid dynamics, and digital modeling, preparing them to revolutionize industrial energy
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metabolism in type I interferonopathies within tissues. Using mouse models of these diseases, we will analyze how metabolic alterations contribute to inflammation and tissue damage. We will generate lipidomic