Centre des Matériaux
Pierre-Marie Fourt
Pierre-Marie Fourt
Lecture
Bio-based aerogels: new eco-friendly porous materials for thermal insulation and controlled release
| Area of expertise | Mechanics |
| Doctoral School | ISMME - Systems Engineering, Materials, Mechanics, Energy |
| Supervisor | M. Pierre KERFRIDEN |
| Co-supervisor | M. David RYCKELYNCK |
| Research unit | Centre of materials |
| Contact | http://www.mat.minesparis.psl.eu/formation/doctorat/propositions-de-sujets-de-these/ |
| Starting date | October 2nd 2023 |
| Keywords | IA, Big Data, system modeling, battery health, electric cars |
| Abstract | In the context of new forms of mobility, knowledge of battery health is a major factor in the electric vehicle ecosystem. Future regulations will impose new health status criteria on automakers, to guarantee controlled ageing at the end of a kilometre and time threshold. The aim of this thesis is to accurately estimate and predict these health criteria using telemetry data from vehicles on the road. Advanced numerical approaches (multiphysics domain, multifrequency, AI on BigData...) will be used during the modeling phases. The predicted states of health will be validated by on-board diagnostics on different vehicles. |
| Profile | Engineer and / or Master of Science - Good level of general and scientific culture. Good level of knowledge of French (B2 level in french is required) and English. (B2 level in english is required) Good analytical, synthesis, innovation and communication skills. Qualities of adaptability and creativity. Teaching skills. Motivation for research activity. Coherent professional project. - Extensive knowledge of artificial intelligence - Mastery of neural networks (recurrent and convolutional in particular) - Mastery of statistics and probabilities, non-convex optimization algorithms, linear algebra - Knowledge of computation on differentiable computational graphs and high-performance algorithms for AI - Knowledge of Big Data, and the challenges of heterogeneous, multi-domain and/or missing data - Knowledge of systems modeling and control, data assimilation (e.g. Kalman filters) - Proficiency in Python Applicants should supply the following : • a detailed resume • a copy of the identity card or passport • a covering letter explaining the applicant’s motivation for the position • detailed exam results • two references : the name and contact details of at least two people who could be contacted • to provide an appreciation of the candidate • Your notes of M1, M2 • level of English equivalent TOEIC to be sent to recrutement_these@mat.mines-paristech.fr and pierre.kerfriden@minesparis.psl.eu |
| Funding | Convention CIFRE |
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