Scientific direction Development of key enabling technologies
Transfer of knowledge to industry

PostDocs : selection by topics

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Polymer synthesis and characterizations of solid-state electrolyte for lithium-ion batteries

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Matériaux

01-02-2020

PsD-DRT-20-0052

laurent.bernard3@cea.fr

LITEN is one of the highest European research centers in the field of the new energy technologies. LITEN research activities focus on the renewable energy, on the energy efficiency and on the high performance materials for energy. Our department is focused on the development of lithium-ion batteries to enhance both simultaneously their energy density and their safety. Standard liquid electrolytes used in actual battery are intended to be replaced by solid-state electrolyte to reach these objectives. The selected candidate will work on patented and exclusive organic materials designed to fulfill all the requirements of solid-state electrolytes. He/she will be in charge of synthesizing new organic and polymer structures. Some steps of the synthesis/process will be carried out under anhydrous conditions (i.e. Glove box or anhydrous room). The post-doc will be in charge of characterizing these materials in terms of structure (NMR, FT-IR, HPLC-MS..), nanostructure (SAXS, POM, XRD, GI-SAXS), physical properties (DSC , TGA, rheology) and electrochemical properties (EIS, cycling, electrochemical stability window measurements). He/she will be in contact with various experts in batteries and large-scale instruments. The project is part of an ANR project with several partners, dedicated to the fundamental understanding of ion diffusion/transport in soft electrolytes by means of multi-scale multi-techniques methodology. Strong and good communication skills (reporting) are expected.

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Numerical Meta-modelization based study of the propagation of ultrasonic waves in piping system with corroded area

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Simulation et Modélisation en Acoustique

01-05-2020

PsD-DRT-20-0055

vahan.baronian@cea.fr

The aim of the ANR project PYRAMID (http://www.agence-nationale-recherche.fr/Projet-ANR-17-CE08-0046) is to develop some technics of detection and quantification of the wall thinning due to flow accelerated corrosion in piping system. In the framework of this project involving French and Japanese laboratories, CEA LIST develops new numerical tools based on finite elements dedicated to the modelling of an ultrasonic guided wave diffracted by the corrosion in an elbow pipe. These solutions support the design of an inspection process based on electromagnetic-acoustic transduction (EMAT). To this end, the ability of CEA LIST to adapt meta-modeling tools of its physical models will be the key asset to allow intensive use of the simulation.

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Measurement of active cell nematics by lensless microscopy

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Systèmes d'Imagerie pour le Vivant

01-03-2020

PsD-DRT-20-0059

cedric.allier@cea.fr

At CEA-Leti we have validated a video-lens-free microscopy platform by performing thousands of hours of real-time imaging observing varied cell types and culture conditions (e.g.: primary cells, human stem cells, fibroblasts, endothelial cells, epithelial cells, 2D/3D cell culture, etc.). And we have developed different algorithms to study major cell functions, i.e. cell adhesion and spreading, cell division, cell division orientation, and cell death. The research project of the post-doc is to extend the analysis of the datasets produced by lens-free video microscopy. The post-doc will assist our partner in conducting the experimentations and will develop the necessary algorithms to reconstruct the images of the cell culture in different conditions. In particular, we will challenge the holographic reconstruction algorithms with the possibility to quantify the optical path difference (i.e. the refractive index multiplied by the thickness). Existing algorithms allow to quantify isolated cells. They will be further developed and assessed to quantify the formation of cell stacking in all three dimensions. These algorithms will have no Z-sectioning ability as e.g. confocal microscopy, only the optical path thickness will be measured. We are looking people who have completed a PhD in image processing and/or deep learning with skills in the field of microscopy applied to biology.

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Application of a MDE approach to AI-based planning for robotic and autonomous systems

Département Ingénierie Logiciels et Systèmes (LIST)

Labo.conception des systèmes embarqués et autonomes

01-05-2020

PsD-DRT-20-0063

matteo.morelli@cea.fr

The complexity of robotics and autonomous systems (RAS) can only be managed with well-designed software architectures and integrated tool chains that support the entire development process. Model-driven engineering (MDE) is an approach that allows RAS developers to shift their focus from implementation to the domain knowledge space and to promote efficiency, flexibility and separation of concerns for different development stakeholders. One key goal of MDE approaches is to be integrated with available development infrastructures from the RAS community, such as ROS middleware, ROSPlan for task planning, BehaviorTree.CPP for execution and monitoring of robotics tasks and Gazebo for simulation. The goal of this post-doc is to investigate and develop modular, compositional and predictable software architectures and interoperable design tools based on models, rather than code-centric approaches. The work must be performed in the context of European projects such as RobMoSys (www.robmosys.eu), and other initiatives on AI-based task planning and task execution for robotics and autonomous systems. The main industrial goal is to simplify the effort of RAS engineers and thus allowing the development of more advanced, more complex autonomous systems at an affordable cost. In order to do so, the postdoctoral fellow will contribute to set-up and consolidate a vibrant ecosystem, tool-chain and community that will provide and integrate model-based design, planning and simulation, safety assessment and formal validation and verification capabilities.

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Non-volatile asynchronous magnetic SRAM design

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Intégration Silicium des Architectures Numériques

01-10-2020

PsD-DRT-20-0069

jean-frederic.christmann@cea.fr

In the applicative context of sensor nodes as in Internet of things (IoT) and for Cyber Physical Systems (CPS), normally-off systems are mainly in a sleeping state while waiting events such as timer alarms, sensor threshold crossing, RF or also energetic environment variations to wake up. To reduce power consumption or due to missing energy, the system may power off most of its components while sleeping. To maintain coherent information in memory, we aim at developing an embedded non-volatile memory component. Magnetic technologies are promising candidates to reach both low power consumption and high speed. Moreover, due to transient behavior, switching from sleeping to running state back and forth, asynchronous logic is a natural candidate for digital logic implementation. The position is thus targeting the design of an asynchronous magnetic SRAM in a 28nm technology process. The memory component will be developed down to layout view in order to precisely characterize power and timing performances and allow integration with an asynchronous processor. Designing such a component beyond current state of the art will allow substantial breakthrough in the field of autonomous systems.

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Detection of cyber-attacks in a smart multi-sensor embedded system for soil monitoring

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Infrastructure et Ateliers Logiciels pour Puces

01-04-2019

PsD-DRT-19-0071

anca.molnos@cea.fr

The post-doc is concerned with the application of machine learning methods to detect potential cyber-security attacks on a connected multi-sensor system. The application domain is the agriculture, where CEA Leti has several projects, among which the H2020 project SARMENTI (Smart multi-sensor embedded and secure system for soil nutrient and gaseous emission monitoring). The objective of SARMENTI is to develop and validate a secure, low power multisensor systems connected to the cloud to make in situ soil nutrients analysis and to provide decision support to the farmers by monitoring soil fertility in real-time. Within this topic, the postdoc is concerned with the cyber-security analysis to determine main risks in our multi-sensor case and with the investigation of a attack detection module. The underlying detection algorithm will be based on anomaly detection, e.g., one-class classifier. The work has tree parts, implement the probes that monitor selected events, the communication infrastructure that connects the probes with the detector, and the detector itself.

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