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of generative watermarking methods, (i.e. to see to which extend the secret key of the watermarking scheme can be estimated). - Help surpervising a PhD student - Security analysis of JPEG steganography - Security
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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experience in large-scale structure simulations, working knowledge of applications of machine learning techniques in cosmology and/or astrophysics (in particular simulation-based inference), strong programming
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cleanroom processes • Overseeing nanofabrication activities within the projects • Training and mentoring PhD students in fabrication techniques and experimental measurements Institut NÉEL is a CNRS unit (UPR
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responsibility. Secondary Activities 1) Contribute to the training of team members (PhD students, interns). 2) Participate in scientific outreach activities. 3) Conduct a scientific watch on advances in fluvial
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ExperienceNone Research FieldPhysics » Surface physicsYears of Research ExperienceNone Additional Information Eligibility criteria A PhD in experimental physics and a background in the study of correlated-electron
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– Paul Sabatier University, as well as several PhD students and postdoctoral researchers, the team provides a stimulating, collaborative, and interdisciplinary research environment. Where to apply Website
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valorization and dissemination of the results.The postdoctoral researcher will also have the opportunity to propose and supervise internships and to contribute to the supervision of PhD students and early-career
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and motivated PhD student to contribute to the development of the next generation of DNA computers, capable of processing large molecular databases. The project will combine concepts from molecular
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part of the IPHC's Department of Analytical Sciences (UMR7178, CNRS / Université de Strasbourg), and comprises around fifty permanent and non-permanent staff (researchers, engineers, PhD students