Internship – M2 – Physical modelling and Machine Learning for microbatteries – Grenoble, France

Job description: As a CEA intern, you will have the opportunity to work in a world-renowned research environment. Our teams are made up of passionate and dedicated experts, providing a stimulating environment for learning and collaboration. You'll have access to state-of-the-art equipment and first-rate research resources to carry out your missions.  CEA-Leti provides integrated microstorage solutions, including solid-state microbatteries. Solid-state microbatteries are among the most promising microstorage technologies for applications in fields as diverse as implantable medical devices and the Internet of Things. This work has given rise to a start-up, InjectPower, whose aim is to industrialize microbatteries for implantable medical devices (CEA-Leti - Injectpower, energy for implantable devices (leti-cea.fr)). Job description: The physical mechanisms involved in the operation of a microbattery are still poorly understood and modelled. To study these components, CEA has a manufacturing and characterization platform dedicated to lithium components. The aim of this internship is to develop a physical model to describe battery performance (voltage, power output) according to conditions of use. The proposed methodology involves : 1.       Use the 15,000 batteries per wafer as test vehicles. Measurements taken during battery cycling are recorded in a database. 2.       Code data processing programs based on machine learning and Bayesian inference methods to highlight optimal cycling protocol parameters. This feedback then feeds into the physical model (validation/understanding/exploration). 3.       Iteration with manufacturing and electrical testing of new battery architectures/designs. For the modeling part, the student will be able to rely on a model describing first-cycle operation (see physical model paper reference). For the database part, a database is under construction and is already fed by electrical tests. A machine learning analysis tool is also under construction to improve the analysis of cycling measurements. Within the LCRE, you will work with a team of 10 people. You will add your touch to missions such as : ·       electrical and electrochemical measurements of microbattery performance, ·       database generation, ·       programming (python or other), ·       simulation using physical models, ·       development of physical models. ·       Subjects can be discussed depending on your school's expectations. Possibility of pursuing a thesis after the internship.

Institute description: The LCRE laboratory develops components for ultra-high-speed radiofrequency applications and all-solid-state energy storage and micro-sources.

Your profile: Vous préparez un diplôme de niveau BAC+5 dans le domaine de la microélectronique, des semi-conducteurs, de la physique de l'état solide ou des micro technologies. Vous possédez des bases solides en design des circuits et des connaissances en programmation et en data science (ou traitement de données). Vous avez encore un doute ? Nous vous proposons : Une expérience à la pointe de l’innovation, comportant un fort potentiel de développement industriel, Des moyens expérimentaux exceptionnels et un encadrement de qualité, De réelles opportunités de carrière à l’issue de votre stage, Un poste au cœur de la métropole grenobloise, facilement accessible via la mobilité douce favorisée par le CEA, Une participation aux transports en commun à hauteur de 85%, Un équilibre vie privée – vie professionnelle reconnu, Un restaurant d'entreprise, Une politique diversité et inclusion. Rejoignez-nous, venez développer vos compétences et en acquérir de nouvelles ! Conformément aux engagements pris par le CEA en faveur de l'intégration des personnes handicapées, cet emploi est ouvert à toutes et à tous. Le CEA propose des aménagements et/ou des possibilités d'organisation pour l’inclusion des travailleurs handicapés.  

Level of qualification studied: Bac+4 - Master 1

Languages: English Fluent