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approach that includes cross-section calculations, the development of Monte Carlo codes, and the advancement of the NanOx model for biological dose prediction. As part of a collaboration with the University
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 24 days ago
Lattice Codes” (BoLaCo) project, a French-German collaboration funded by the ANR and the DFG, in partnership with Prof. Jens Eisert’s group at Freie Universität Berlin. The project aims to develop new
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to developing an entirely new data storage platform, encompassing coding, synthesis, and readout capabilities. Additionally, it involves the integration of three CY University laboratories. The proposal
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163 rue Auguste Broussonnet Postal Code 34000 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone YahooMail
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chemistry in 2D PIC/MCC code and participate in the code validation by comparing simulation results with experimental data provided by COMHET collaborators working on iodine-fueled HETs. - Participate in
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-tested code. * Coordinate cross-site integration within an ANR project consortium (Lyon – Marseille -Strasbourg) involving laminar MEG (Lyon), laminar NHP electrophysiology (Marseille), and computational
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-source framework, enabling the systematic study of these materials. The work will involve developing tensor network numerical codes, building upon existing libraries and codes, to study general models
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: The primary focus of this position is to develop concentration inequalities in the nonstationary setting, specifically for periodic Markov chains and periodic time series. Responsibilities also include coding
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(currently at Southampton University) and with data processing experts in the MATISSE international consortium. Her/His first main task will be to combine the existing image reconstruction codes
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periodic time series. Responsibilities also include coding the proposed algorithms in R or Python, such as methods for splitting periodic time series into regeneration blocks, and applying them to real