147 structures-"https:" "https:" "https:" "https:" "University of Minho" PhD positions in France
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. Argument(ation) mining, the new and rapidly growing area of Natural Language Processing (NLP) and computational models of argument, aims at the automatic recognition of argument structures in large resources
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electronic structure methods for the above-described properties. In more details, this will require the development of an automated approach that allows identifying the excited-states across several levels
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concerns about external validity and equity, as underserved groups are often underrepresented due to restrictive eligibility criteria and structural barriers to participation. Even when included, patient
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The expert will participate in the necessary methodological developments and analyses of airborne data recorded by the IAGOS research infrastructure (https://www.iagos.org ) and from other networks, to provide
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. LipidBRIGHT builds on available patient cohorts, advanced technologies and established cooperations and strives to synergistically improve structural training on European level. LipidBRIGHT will nurture the
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; Giauque et al., 2023). The PhD work is structured around the following key milestones: 1. Implementation and validation of real-gas model: Develop, verify and validate real gas equations of state capable
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on structural data. More information and applicaiton : https://positions.stradivarious.eu/jobs/6722909-dc11-ehec-type-iv-pili-structure-host-adhesion-and-signalling
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al. 2019] and point-force Lagrangian models, with advanced post-processings [Vegad2024]. This work will be carried out with the YALES2 high-performance platform. Where to apply Website https
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the Universities of Salzburg and Maastricht. One position includes an additional computational component, and the other a focus on transcranial brain stimulation. Where to apply Website https
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, L. Estel, Analysis of thermal runaway events in French chemical industry, Journal of Loss Prevention in the Process Industries, 62 (2019) 103938. https://doi.org/10.1016/j.jlp.2019.103938 2. Y. Wang