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several members will meet with candidates and ensure optimal conditions for a successful interview. Application deadline: 14/02/2026 Indicative interview period: 24/02/2026 Desired starting date: 01/04/2026
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mechanistic features will be deciphered in order to fully understand the cleavage reaction of DNA with DNAzymes. Sample preparation (DNA both as catalyst and substrate), followed by optimization of pulsed EPR
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. To that aim, both Stein-based bilevel optimization, empirical Bayesian and unsupervised deep learning approaches will be considered. The recruited postdoc researcher will tackle both implementation challenges
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determining the optimal culture conditions (e.g. culture media, light intensity and temperature) and establishing the feasibility of transferring existing protocols to these species. Description of tasks
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polymer blending and colloidal lithography. Low-cost fabrication processes will be developed and optimized, and their performance will be analyzed using optical spectroscopy. Results will then be compared
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testing of concrete structures Good Knowledge of data science, e.g. optimization, machine learning, and structural sensing technologies Openness to interdisciplinary research and commitment to teamwork
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. The BERNARDO project aims to meet this challenge by designing nanostructures optimized to maximize these observables and by establishing fundamental connections between near-field and far-field chiral phenomena
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disease ⎯ Establish and optimize 3D culture models to explore endothelial–epithelial cross-talk ⎯ Perform imaging and spatial transcriptomics; contribute to data analysis & interpretation ⎯ Write and
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reduces the energy cost, save water, recycle metals limiting economic dependence and preserve resources. The project aims to optimize the process and extend the applications in direct relation with
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learning and statistics. A good command of Python programming is essential, as is a good command of English, both spoken and written. Skills in optimal transport theory and knowledge of generative models