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: This project is an interdisciplinary effort at the frontier between Biology (Genetics, Genomics), Bioinformatics, Artificial Intelligence (Neural Networks) and Statistics (LMMs). The aim is to join the
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• Develop, consolidate, and optimize fMRI and EEG neurofeedback algorithms. • Design, integrate, and test standalone neurofeedback software (software suites for clinical environments). • Contribute
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karstic networks and alluvial terraces lying on the top of the foothills. The work will be mainly based on already existing and new TCN dates in order to: (1) gain an overview of the oldest remaining
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physics is especially interesting due to the presence of exotic excitations, potentially non-Abelian. The TensQHE project aims to develop modern numerical tools based on tensor networks, within an open
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Eligibility criteria PhD in Materials Science, Process Engineering, or a similar field. Required Skills: Proficiency in ceramic and composite material development processes, as well as structural, mechanical
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polariton accelerator” will exploit exciton–polaritons to implement artificial neural networks directly in hardware rather than in software. Exciton–polaritons are hybrid quasiparticles composed of light
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of quantum information science, tensor network theory, and generative modeling (transformers, diffusion models, etc.). - Conduct cutting-edge research at the intersection of quantum information, machine
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of ethical and regulatory files. • Contribution to the collaborative development of neurofeedback software (user interface, usability feedback). • Participation in team meetings and regular exchanges with
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the synthesis of the nanowires and their assembly into networks (by soft chemistry), while the synthesis of the matrix (CVD deposition) will mainly be carried out by a PhD student already recruited
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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