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

PostDocs : selection by topics

Application of ontology and knowledge engineering to complex system engineering

Département Ingénierie Logiciels et Systèmes (LIST)

Labo. ingénierie des langages exécutables et optimisation



Model-Based System Engineering relies on using various formal descriptions of the system to make prediction, analysis, automation, simulation... However, these descriptions are mostly distributed across heterogeneous silos. The analysis and exploitation of the information are confined to their silos and thereby miss the big picture. The crosscutting insights remain hidden. To overcome this problem, ontologies and knowledge engineering techniques provide desirable solutions that have been acknowledged by academic works. These techniques and paradigm notably help in giving access to a complete digital twin of the system thanks to their federation capabilities, in making sense to the information by embedding it with existing formal knowledge and in exploring and uncovering inconsistencies thanks to reasoning capabilities. The objective of this work will be to propose an approach that gives access to a complete digital twin federated with knowledge engineering technologies. The opportunities and limits of the approach will be evaluated on industrial use cases.

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Development of a cell analysis algorithm for phase microscopy imaging

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Imagerie et Systèmes d'Acquisition



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 is to extend the analysis of the datasets produced by lens-free video microscopy. The objective is to study a real-time cell tracking algorithm to follow every single cell and to plot different cell fate events as a function of time. To this aim, researches will be carried on segmentation and tracking algorithms that should outperform today's state-of-the-art methodology in the field. In particular, the algorithms should yield good performances in terms of biological measures and practical usability. This will allow us to outperform today's state-of-the-art methodology which are optimized for the intrinsic performances of the cell tracking and cell segmentation algorithms but fails at extracting important biological features (cell cycle duration, cell lineages, etc.). To this aim the recruited person should be able to develop a method that either take prior information into account using learning strategies (single vector machine, deep learning, etc.) or analyze cells in a global spatiotemporal video. We are looking people who have completed a PhD in image processing, with skills in the field of microscopy applied to biology.

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Characterization of X-ray emitting radionuclides - Application to reactor dosimetry

Département Métrologie Instrumentation et Information (LIST)

Laboratoire de Métrologie de l'Activité



The activity measurement of X-ray emitting radionuclides in the energy range below 100 keV encounters several difficulties that limit the accuracy of the result. These include the difficulty of calibrating detector performance and, in general, the significant uncertainties associated with emission intensities X. In addition, the self-absorption effects of X-rays in standard sources or samples lead to important corrections that must be controlled. Among the important applications of X-emitter measurement, reactor dosimetry, which makes it possible to determine the neutron fluence received during irradiation and to characterize its spectrum, is based on the analysis of the activity of irradiated dosimeters. These are made of pure metals or alloys of perfectly known compositions, some of which are activated or fissioned by neutrons. For example, reactions 93Nb(n,n')93Nbm and 103Rh(n,n')103Rhm are of prime importance for reactor dosimetry and are particularly interesting for characterizing neutron fluxes around 1 MeV. The proposed work follows a thesis that identified several areas for improvement in dosimeter measurement that will need to be implemented, including : - improvement of radionuclide X-ray emission data used as standard for calibration (133Ba, 152Eu, etc.) to establish a consistent set of data; - validation of corrective coefficients due to the presence of impurities during dosimeter irradiation; - evaluation and publication of the decay scheme of 103Pd and 103mRh; - implementation of a new method of performance calibration using monochromatic radiation.

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Compressed Sensing for ultrasonic imaging: disruptive method development and prototyping

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Méthodes CND



In non-destructive ultrasonic testing, multi-element sensors are used for the inspection of structures to ensure the safety of people and infrastructures. Currently, one of the driving factor of an ultrasonic method is the number of elements of the sensor, influencing the speed and efficiency of the inspection but also the cost and the volume of the equipment. This project aims at developing a prototype of a multi-element sensor with a limited number of elements compared to current state of the art equipment, without losing imaging resolution. To achieve this goal, Compressed Sensing (CS), a recent technique of signal processing allowing to go beyond the traditional sampling theorems and to reconstruct data from severely undersampled measurements, will be used. The ultrasonic inspection procedure will need to be entirely rethought to meet the CS requirements, specifically the sparsity of the measured data and the incoherence of the measurement process. The expected results is a significant reduction (of the order of 5) of the number of elements to conduct imaging, which would be a true revolution in NDT with direct applications in various industrials sectors. The following laboratories, all located in Saclay (France) of the CEA (the French atomic commission), will participate to the project: the NDT department for its expertise in multi-element ultrasonic testing and Neurospin and Cosmostat for their expertises in the field of CS, mainly applied to medical RMI imaging and astrophysics, respectively. The collaboration between these three labs, each among the worldwide leading institutes in their respective fields, will ensure the creation of a new and disruptive family of sensors.

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Nanophotonics applied to ultrasensitive biomolecular detection

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Chimie des Matériaux et des Interfaces



This project proposes to develop an array of highly sensitive and specific detectors, based on nanowire photodetectors to target single molecule detection (SMD) and biological analysis applications involving a protocol without amplification. Nanowire arrays have the potential to improve the detection limit of DNA strands functionalized with quantum dots markers, without the need for amplification. They are CMOS compatible and will allow ultra-compact integration. Thanks to their fast response and the ability to create dense arrays over large areas, nanowire photodetector are therefore an interesting approach to detecting rare events (SMD). Nanowire geometry is an interesting approach to optimize the speed-response trade-off. The first objective of this project will be to explore the physical mechanisms that determine the performance of semiconductor nanowire photodetectors at the level of a single nanowire and then on an array of nanowire photodetectors. The biofunctionalization of this array and its hybridization with labelled DNA strands will be explored.

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Apprenticeship Learning Platform deployment for industrial applications





This project aims at developing a demonstrator that integrates state-of-the-art technologies and improve it on a use-case representative of the industrial world. The demonstrator will consist in a robotic / cobotic arm coupled to an acquisition sensor (RGBD type). This device will be positioned in a workspace made of a rack / shelf containing objects / pieces of various shapes and qualities (materials, densities, colors ...) in front of which will be placed a typical conveyor prototype of industrial installations. The type of tasks expected to be carried out by the demonstrator will be "pick and place" type tasks where an object will have to be identified in shelf and then placed on the conveyor. This type of demonstrator will be closer to the real industrial conditions of use than the "toy" examples used in the academic field. This demonstrator will focus first on the short-term effectiveness based on state of the art technologies for both hardware and software, for a use case representative of the industrial world. At first, it will thus be less focused on the evolution of the algorithms used than on the adaptation of the parameters, the injection of knowledge a priori dependent on the context making it possible to reduce the high-dimensional input space, etc.

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