Construction of databases for radionuclide identification based on neural networks (NANTISTA project)
The project NANTISTA (Neuromorphic Architecture for Nuclear Threat Identification for SecuriTy Applications) deals with the prevention of illegal traffic of nuclear materials at international borders. The project aims at the development of a detection platform using plastic scintillators for fast radionuclide identification (such as fissile materials) based on neural networks. The post-doctoral subject consists in the development of the detection system and the construction of databases dedicated to the learning process and the optimization of the neural networks. The databases will be built with experimental measurements given by radioactive sources. Radiation-matter simulations (Monte-Carlo codes Geant4 and Penelope) will also be implemented for the construction of the databases.
Design and implementation of force feedback by electrical sense for remote operation with submarines or aerial robots
Since few years, the Bio-inspired Robotics group of the IRCCyN Robotics team is developing a bio-inspired perception mode found on some freshwater tropical fish: the electrical sense. This active sense is based on the distortions measures, due to environment, of an electric field produced by the fish. Based on this principle Irccyn developed in the context of a European project called Angels, the first autonomous underwater robot capable of moving by means of the electrical sense . In the future, CEA TECH and Irccyn want to extend this first result in multiple directions, including the remote operation of submarines manipulators and aerial robots domains. The force feedback should be emulated by the use of the electrical sense. Integrated in the Bio-inspired robotics team of IRCCYN , post -doctoral fellow will contribute to the development of the electric sense and its use for underwater and aerial teleoperation . He will participate in the design and development of new sensors inspired by electric fish and their use for underwater telerobotics. The results of its work will underpin the industrial demonstrator system (teleoperation offshore) to be developed under the project CEA TECH / IRCCYN Bio-inspired robotics.
Development of new spectrometric methods for the characterization of uranium-bearing ore
This subject aims at developing new methods of X/gamma-ray spectrum analysis for the characterization of uranium-bearing ore, enabling to process data obtained in the framework of nuclear mining activities. This subject will be developped into two parts. The first part will concern the processing of complex gamma-ray spectra, obtained using different types of medium-resolution scintillators (such as NaI or LaBr3 detector). The main purpose of this part will be related to the processing of complex regions of interest using deconvolving methods by non-parametric Bayesian inference, notably by using the SINBAD code, initially developed by CEA LIST for the processing of HPGe spectra. The second part of the subject will concern the analysis of low-resolution spectra obtained using a NaI detector in order to obtain a spectrometric information. In this case, a traditional approach based on the analysis of photoelectric peaks is not conceivable. The problem will be studied in the form of an inverse problem using a model of the detector response and a reconstruction, using an approach analogous to computed tomography. The performances of different types of reconstruction algorithms will be studied (EM analysis, non-parametric Bayesian approach).
Compressed Sensing for ultrasonic imaging: disruptive method development and prototyping
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.
Compensation methods (for magnetic perturbation) for shape capture via orientation sensors
Our laboratory works for several years on shape capture (curves, surfaces) in static and moving positions, via inertial sensors - e.g. accelerometers ans magnetometers - able to provide information about their own orientation. In fact, in real conditions, sensors do not exactly provide their orientation, the measure is disturbed with external contributions (own motion acceleration, vibrations, magnetic perturbations). This work consists in analysing these disturbances, proposing preprocessing to clean data to obtain "denoised" tangential information to allow the reconstruction of these curves and surfaces.
First, we study the case of the reconstruction of a metallic pipe: we want to reconstruct a curve with magnetic sensors disturbed (the surface reconstruction will be explored afterwards). This work consists in finding the best methods allowing to extract the needed information from these "noised" signals (data fusion, source separation, model of perturbations, adding a new sensor modality,... are domains to explore). In this goal, a bibliographic study will be done firstly by the Post Doc student, then he will have to implement the different methods found, and test the performances with real signals acquired with our system of shape capture in a disturbed environment.
In situ analytical device based on the LIBS technique for the characterization of hard environment liquid media
The proposed research project aims at developing an in situ analytical device based on the LIBS technique for the characterization of hard environment liquid media such as high temperature melting materials or highly volatile liquid metals used for development of low carbon energy production. The project involves two CEA teams specialized in LIBS instrumentation, analytical developments and high temperature environments.
At high temperature, the molten metals have a high surface reactivity leading to processes of oxidation, slagging … Non-intrusive analysis of this surface by traditional LIBS tools leads to a non-representative results of the molten metal chemical composition. In this project, a new-patented concept based on a mechanical stirring coupled to the LIBS device is developed in order to have a renewable and stable surface of the liquid metal. The aim is to have an on-line representative composition of the metal during the treatment process. The developed demonstrator will be validated for the analysis of impurities (at ppmw ranges) in liquid silicon (T> 1450 °C) during the purification process and the crystallization one for photovoltaic applications. At the end of the project, recommendations for in-situ analysis of liquid sodium (used as cooling fluid in nuclear reactors) will be given.
Electrical characterization of phase-change memories (PCM)
Main objectives of this postdoc position will be the electrical characterization in view of basic physical modelling of chalcogenide materials and integrated devices for application to sub-45nm embedded Phase-Change Non-Volatile Memories.
Electrical characterization (program dynamics, data-retention at different temperature, cycling, data-retention after cycling, disturb during cell reading and programming of nearby cells...) on test structures will be performed in order to put in evidence the main performances and degradation modes. Electrical characterization on blanket deposition will be operated as well, in order to assess the chalcogenide resistivity, crystallization temperature and thermal conductivity.
The postdoc will be involved in a detailed experimental work, but he will have also to face the theoretical principles governing the functionality of a Phase-Change Memory. In particular, the obtained experimental data will be coupled to a basic physical modeling of the chalcogenide materials integrated in the test structure, considering the electrical & thermal dynamics governing the phase change process of PCRAM devices.
Correlative X-ray and ToF-SIMS tomography Data fusion of 3-D data sets from X-ray and ToF-SIMS tomography
The nanocaracterisation platform of the CEA Grenoble has recently installed 2 state-of-the-art tools for 3-D imaging with 100 nm resolution: X-ray tomography in a SEM and time of flight secondary ion mass spectrometry (ToF-SIMS) assisted by focused ion milling (FIB). X-ray tomography delivers non-invasive 3-D images of the internal morphology of an object whilst ToF-SIMS is able to map the local composition in 3-D. We aim to combine the two techniques to perform quantitative 3-D investigations of objects such as copper pillars for microelectronics or silicon electrodes for Li battery applications.
The proposed research subject is data analysis orientated. Some simulation work may be performed to implement and test existing 3-D data fusion methods with a view to adapting and improving them. The candidate will assist with the experimental measurements and be responsible for treating the data with the chosen protocols. The candidate should be pragmatic, at ease with applied mathematics and have good programming skills. These will be essential in understanding and manipulating the fusion and reconstruction algorithms, from the simplest, to the increasingly advanced (prior information, superiorisation, Bayesian fusion)
The candidate will have completed a PhD in physics and have good computer (Python, Matlab, C) and image treatment skills, or a PhD in mathematics/computational science with an interest in applications. The candiate will need to interface with a multidisciplinary team, and be receptive to new ideas. The candidate will be proficient in both written and spoken English in order to communicate with the team and to disseminate their results in articles or at conferences.
Electrical Characterization of resistive memory devices
The activity of the postdoc will be focused on electrical characterization and physical modeling of devices with integrated bistable oxides (ie NiO, HfO2): mainly he will address both the hardware & methodology to address the non-volatile memory performances (ie write/erase, data retention and endurance), and he will perform measurements on several devices featuring different bistable oxides (ie NiO, HfO2…). Note that particular attention will be devoted to pulsed measurements tailored for “non-polar” or “bipolar” devices. After having collected sufficient ensemble of data on memory performance, he will try to interpret them in the simplest form with possibly semi-analitycal models in order to catch the basics of physics relying behind the electrical data.