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Field
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concerned, among other things, with the effects of images and the mechanisms that make up communication with images. Key questions are: Who produces images and for whom? What message do these images convey
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to design and implement research projects. Support nanoformulation and in vitro characterization workflows. Train in cryo-TEM sample preparation, imaging, and interpretation, leading Nanoworx’ efforts in
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functional aspects of the olfactory system in amphibians and other aquatic vertebrates. Using advanced imaging, neurophysiological, and molecular biological methods, we investigate the olfactory system
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approaches (overexpression, invalidation), transcriptomics (bulk RNAseq, single cell RNAseq), biochemistry and imaging, as well as bioinformatic analyses. This project should enable the identification of key
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grounding, in other words, the linking of elements of natural language (words, phrases, or sentences) to visual inputs (such as images or video) in a meaningful way. The position is part of an on-going
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, including patch-clamp electrophysiology, high-resolution imaging, chemogenetic manipulation of glial activity, and behavioral assays in rodent models Analyze and interpret complex datasets from
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Programming experience in Python Excellent communication skills and fluency in English Collaborative personality with attention for detail Experience in imaging or spatial omics data analysis Background in
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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paradigm for quantum optimization with quantum computing (QAOA, Quantum annealing, etc.) Knowledge of quantum computing SDKs such as Qiskit or Pennylane We offer Multilingual and international character
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for understanding natural magmatic processes on earth & other planetary bodies. Neutron diffraction is a powerful technique for studying the atomic scale structure of these materials, but the current technology to