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macroscopic designs for soft-tissue healing. The project will be conducted using in vitro models of bacterial adhesion and fibroblast proliferation in collaboration with University of Gothenburg and in vitro
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' genomes model. This 'two-speed' genome model stipulates that the genome is composed of two compartments with different architecture, content and speed of evolution. The first compartment, composed of core
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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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disease models. The project offers training at the crossroads of protein engineering, structural biology, and cancer biology, and will provide the candidate with a strong interdisciplinary skill set that is
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turbulent plasmas and by phenomenological models. The overarching goal of this ambitious programme is to describe the acceleration process across length scales, in the turbulent flow, in the inner jet and in
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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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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