Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
-
predict interaction effects. Unlike robot-specific neural network models, the proposed approach aims to learn a universal representation of local interactions (fluid-structure, robot-robot, robot-object
-
model introduced previously for carburizing will be further developed in this study. In this model, carbon diffusion is predicted using Fick's law and finite difference scheme. A source term accounts for
-
predictive models of immune responses. Develop advanced and innovative machine learning methodologies and analyze data. The postdoctoral researcher will join the groups of T. Mora and A. Walczak, whose
-
velocity anomalies (Vp, Vp/Vs). These observations will be quantitatively compared with model predictions to test whether the system is dominated by the geometric interactions of the faults, the rheological
-
, France to complete the project. Objectives The objective of this PhD project is to develop advanced numerical modelling tools to support the digital twins of refractory materials, with the aim
-
rate and will receive partial reimbursement for public transportation fares if necessary. Despite the spectacular success of AI-based approaches for protein structure prediction, reliable 3D modeling
-
tomography, high-pressure reactor) with numerical modelling (COMSOL) to quantify and predict dissolution. • Select and characterise biogenic shells (foraminifera, pteropods) from oceanographic cruises
-
generation, targeted atomistic simulations, structural descriptor extraction, and predictive models. The work will aim to establish links between local pore geometry, structural disorder, sodium adsorption
-
of the MOST (Modelling and Simulation of Turbulence) team focus on the numerical prediction of turbulent and multiphase flows with a broad range of objectives from fundamental understanding of flow properties