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

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Combinatorial optimization of base materials for the design of new materials

Département Métrologie Instrumentation et Information (LIST)

Laboratoire Intelligence Artificielle et Apprentissage Automatique

01-02-2021

PsD-DRT-21-0057

jean-philippe.poli@cea.fr

The design of new materials is a field of growing interest, especially with the emergence of additive manufacturing processes, thin film deposition, etc. In order to create new materials to target properties of interest for an application area, it is often necessary to mix several raw materials. A physicochemical modeling of the reactions that occur during this mixing is often very difficult to obtain, especially when the number of raw materials increases. We want to free ourselves as much as possible from this modeling. From experimental data and business knowledge, the goal of this project is to create a symbolic AI capable of groping for the optimal mixture to achieve one or more given properties. The idea is to adapt existing methods of operations research, such as combinatorial optimization, in a context of imprecise knowledge. We will focus on different use cases such as electric batteries, solvents for photovoltaic cells and anti-corrosion materials. Within the project, you will: ? Study the state of the art, ? Propose one or several algorithms to prototype, and their evaluation, ? Disseminate the resulting innovations to the consortium and the scientific community, through presentations, contributions to technical reports and / or scientific publications. Maximum duration: 18-24 months (regarding your experience).

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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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Wood modifications by supercritical CO2

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire des technologies de valorisation des procédés et des matériaux pour les EnR

01-04-2021

PsD-DRT-21-0062

pierre.piluso@cea.fr

In order to replace current high environmental impact construction materials, CEA leads research work on chemical functionalization of wood (from French local forests) to improve its properties and make them a viable substitute of these construction materials or imported construction wood. In this frame, chemistry under supercritical CO2 appears to be an efficient way to carry innovative chemistries while liùmiting the environmental impact & VOCs emissions of such processes. Thus, you will be in charge of the development of new processes of chemical modification of local wood species under supercritical CO2. You will lead the research project by perfroming the state of the art, making technical propositions (around the adapted functionalization chemistries), carrying out the eperiments & the characterizations and will be in charge of respecting the deadlines & redacting the associated deliverables.

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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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Formalization of the area of responsibility of the actors of the electricity market

DSUD (CTReg)

Autre DPACA

01-06-2020

PsD-DRT-20-0074

bruno.robisson@cea.fr

The CEA is currently developing a simulation tool which models the energy exchanges between the actors of the electricity market but which models, in addition, the exchanges of information between those actors. The first results of this work show that, for some new energy exchange schemes, 'indirect' interactions between actors may appear and may cause financial damage (for example, the failure of a source of production of one actor may impact the income of another). Thus, the borders which clearly delimited until now the areas of responsibility of each actors could be brought to blur and their areas of responsibility could "overla". The candidate will be responsible for: - Formally define the area of responsibility of an actor in the electricity market, - Model the interactions, including 'indirect' ones, that may appear between these actors, - Apply formal proof techniques (such as 'model-checking') to detect overlaps in areas of responsibility, - Define the conditions of exchange between the actors which would guarantee the non-recovery of the areas of responsibility.

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