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- improving the GEANT4 simulation of the ALERT detector, - conduct data analysis in the ALERT group, - participate in hardware developments for the ePIC Roman pots, - develop an analysis within the exclusive
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neuromorphic and energy-efficient hardware architectures. Early concepts – such as Intel's MESO logic gate – illustrate the transformative potential of multiferroic technologies and motivate deeper scientific
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selection and switching in real time Integrate surrogate models with physics-based solvers, e.g. SOFA, FEniCSx, SOniCS, and clinical or phantom data Deploy models on ARSPECTRA hardware, including optimisation
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, depending on your skills, integrating hardware accelerators (FPGA) into "Hardware-in-the-Loop" simulations. Finally, you will actively participate in the scientific dissemination of the work through the
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of the project is to design, model and simulate neural networks based on magnetic skyrmion nucleation and propagation. The second objective is to fabricate these hardware neural networks, characterize
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, robot control, unconventional cameras, humanoid robotics Skills: formalization of geometric and photometric image models, neural network training, software development, hardware installation, oral and
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on ARSPECTRA hardware in collaboration with their engineering team Contribute to open-source code, demonstrators and joint publications with ARSPECTRA and clinical partners Your profile PhD in computational
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be defined at two levels: SAACD Component: This is a UAV made up of hardware and software sub-systems, capable of observing, predicting, deciding and reconfiguring itself to fulfil its mission (e.g