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concurrently heated with an additional external stimulus. Photoacoustic sensing (introductory video: https://youtu.be/2f3V0DQNLYg ) is based on a transformation of absorbed optical energy into ultrasound waves
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. These include structured data (e.g., GPS coordinates, temperature, humidity), semi-structured inputs (e.g., XML/JSON sensors feed), and unstructured content (e.g., images, videos, audio, human input via voice
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6-24): Construction of autoencoders for compression of high-dimensional fields. Sparse identification (SINDy) or genetic programming (GEP) for derivation of explicit, interpretable control laws
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information into a stable HD code anchored to visual landmarks. Neurons in different PrS layers have distinct targets, and we will be particularly interested in the intrinsic bursting neurons of layer 4, which
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implementation of models of the plasmonic response – both linear and non-linear – based on the equations of quantum hydrodynamics (QHD), the implementation of the corresponding numerical codes and their
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the literature, as has been done in Bey-Zekkoub et al. (2025). The developed code will enable contaminants to be traced. Finally, using an inverse problem approach, the model will also make it possible to identify
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will work directly with Prof. Aurélie Perrier, specialist in computational photochemistry, and will interact closely with all members of the SIMULACTOR consortium. The quantum chemistry codes required
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-field code, written in the Cuda C language and parallelized on a single GPU (Graphical Processor Unit). A parallelization on multiple GPUs would be a welcome development during the thesis. Where to apply
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will use and develop Python scripts for analysing results and may participate in the development of codes such as the observation simulator and the improvement of the controller. The proposed thesis will
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relevant to the field - programming/coding in Python (Pytorch) - presentation of results at conferences - interaction with team members and international collaborators Degree : Master of Physics, data