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Field
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design projects in a transdisciplinary way while deepening one's own field of expertise. A specific teaching programme will be offered and the doctoral students concerned will also have the opportunity
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Université has selected the IRV (Illustration, Representation, View) project, headed by Stéphane Lojkine, to develop the Utpictura18 database and website. IRV plans to fund a 36-month doctoral contract
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need to be perfectly understood and predictable. Industrial scale non-destructive sensoring combined with machine learning algorithms will then be implemented to develop an accurate numerical model
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quantified. The experimental part of this project will be used to calibrate the mathematical model developed by our partners in Grenoble (TIMC). The aim is to develop a model for predicting cell dynamics
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defects beneficial for the electron and ion transport properties. The thesis subject will lead the candidate to develop its skills in solid-state chemistry, electrochemistry and device fabrication
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brings together Universities and Research Centres with the end goal of improving current knowledge of the physics of coupled phenomena in the subsurface. Key target of the project is to develop a unique
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of the key problems stems from the difficulty of characterising and controlling the catalytic interface under working conditions. This thesis will develop new tools to control catalytic reactions on demand. In
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fundamental problem is fusing heterogeneous datasets containing dataset-specific information. The objective of the project is to develop flexible and directly interpretable unsupervised learning algorithms
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adjacency matrix of a graph 𝒢, where the edges represent the coefficients a_{ij} for i ≠ j, and the nodes represent the coefficients a_{ii}. We then train a Graph Neural Network (GNN) to predict without
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complex quantum physical concepts to develop meaningful ab initio models. A good understanding of the mechanisms involved in prospective spintronic devices will be preferable to identify the best materials