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: Development of advanced BLR models, constrained by precise SA measurements, enabling dynamical modelling of RM data to better constrain geometry and kinematics, and thereby control systematic biases. • Data
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Cancer, Neurological and Infectious Diseases. Biomolecules, 2023. 13(5).https://www.mdpi.com/2218-273X/13/5/737 [2] Vuillemot, R., et al., MDSPACE: Extracting Continuous Conformational Landscapes from Cryo
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. Molecular Mechanisms Driving and Regulating the AAA+ ATPase VCP/p97, an Important Therapeutic Target for Treating Cancer, Neurological and Infectious Diseases. Biomolecules 2023; 13: 737. https://doi.org
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 1 day ago
development: Hybrid Graph-Relational View Replication. We will develop a formal foundation for replicated hybrid graph–relational views that captures how derived data should evolve and compose across
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PhD position: Nanoengineering refractory compositionally complex alloys for extreme conditions (M/F)
of the materials. Complementary structural and micromechanical characterizations will be carried out after irradiation to analyze the evolution of microstructure and properties. The objective is to establish
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batteries have enabled the development of portable electronics and electric vehicles, due to their great gravimetric and volumetric energy densities. The tremendous success of these systems and the
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generalized parton distributions (GPDs). A key component of the PhD will also involve the development of novel algorithms designed to overcome current computational and theoretical challenges in hadron
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between contaminants, • the potential role of PFAS and antibiotics in the selection of antibiotic resistance genes (ARGs). The successful candidate will contribute to the development of an integrated urban
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development in preterm infants using 3D ultrasound imaging. The project relies on a multicenter dataset of more than 300 patients collected from 10 hospitals. The objective is to develop supervised learning
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of this brain cancer, as well as the evolution of the tumor. This part of the project involves designing, developping, and running machine learning algorithms and approaches to exploit vectors of RNA modification