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

PhD : selection by topics

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Edge-IA autonomous systems for biodiversity protection

Département Systèmes (LETI)

Laboratoire Autonomie et Intégration des Capteurs

01-10-2021

SL-DRT-21-0808

esteban.cabanillas@cea.fr

Cyber physical systems - sensors and actuators (.pdf)

Within the framework of technological development for biodiversity protection, measurement tools to precisely quantify the impact of human activities (agriculture, wind turbines, antennas, urban sprawl, etc.) and strategies implemented for biodiversity protection have yet to be developed. The proposed thesis aims to overcome this lack by proposing to develop an autonomous and reliable on-board electronic system for monitoring and quantifying biodiversity. The thesis will be based on advanced technological solutions using edge artificial intelligence (edge AI), energy harvesting and energy management (photovoltaic modules, battery, energy management circuit), data processing from various sensors (audio, video) and low-power electronics (hardware and firmware), particularly for data processing and communication aspects. The core of the thesis will therefore focus on minimising the hardware and firmware energy consumption of embedded electronic systems implementing artificial intelligence for the application "monitoring and protection of biodiversity". A complete electronic device (hardware + firmware) implementing these innovations and deployed in real situations is expected by the end of the thesis.

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novel integrated circuit topologies using innovative capacitive components on silicon

Département Composants Silicium (LETI)

Laboratoire Stockage et Microsources d Energie

01-10-2021

SL-DRT-21-0814

sami.oukassi@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

The objective of this thesis is to assess the potentiel of hybrid silicon capacitors developed at LETI as components in novel architectures of integrated energy conversion circuits. The hybrid capacitors exhibit a combination of unique properties in terms of energy density (ionic storage of the order of 40 mJ / mm3) and frequency response (dielectric storage demonstrated up to 30 GHZ), in addition to a technological realization on 200 mm silicon wafers. Within the framework of this project, it is proposed to design energy conversion circuits (eg. DC-DC converters)exploiting the intrinsic properties of the hybrid capacitors developed at LETI.

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Development of an operando gas analysis setup for all-solid-state batteries and study of the impact of doping on electrolyte stability

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

Laboratoire Analyse électrochimique et Post mortem

01-09-2021

SL-DRT-21-0815

irina.profatilova@cea.fr

Electrochemical energy storage incl. batteries for energy transition (.pdf)

Doctoral project will focus on the development of the characterization setup for all-solid-state batteries and conducting operando gas analysis for development of safer solid electrolytes. All-solid-state batteries represent a cutting-edge field of the development of modern batteries for electric transportation of the future. First precommercial batches of solid cells with sulfide electrolyte have been demonstrated by Samsung (cycle life: >1000 cycles). However, there is still a lot of issues to understand and solve for further wide commercialization of this type of batteries. The main obstacle for sulfide-based electrolytes is their instability vs humidity. Another problem is related to the possible gas evolution during cycling. Characterization methods for all-solid-state batteries are in the early stage of their development. There is a high demand for scientific tools and methods for investigation of various effects leading to gas generation inside the batteries and their degradation, which is directly related to their safety. The objectives of the present project are 1) development of the experimental setups for a precise study of reactions of solid electrolytes leading to gas generation in various conditions and 2) obtaining of improved electrolyte for solid batteries based on the deep understanding of its reactivity. There are three principal interconnected parts: construction and improvement of setups, conducting of fine analysis of electrolytes and synthesis of an improved solid electrolyte sample. The project will be done in French Commissary of Atomic and Alternative Energies (CEA) located in Grenoble. It is known for its excellent set of equipment and expertise in the research and development of greener energy, notably in batteries. This center offers an opportunity to join a dynamic team and to conduct a high-level research in a multidisciplinary environment. Grenoble area is a famous hiking and skiing resort. We are looking for a motivated and pro-active candidate for a Ph.D study starting in autumn 2021 for 3 years. There is a health insurance for the foreigners. Good oral and written English as well as capability to make literature reviews and write papers are essential. The experience acquired by the student during the Ph.D study will be undoubtedly of high interest for further employment.

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Qualitative reasonning and design of complex systems

Département Ingénierie Logiciels et Systèmes (LIST)

Labo. ingénierie des langages exécutables et optimisation

01-04-2021

SL-DRT-21-0823

jean-pierre.gallois@cea.fr

Numerical simulation (.pdf)

The design of complex systems is an activity that affects many industrial and research fields. This implies difficulties in modeling and simulating by the heterogeneous nature of the data involved, with discrete and continuous aspects. Two approaches are possible. Quantitative methods, whose analyzes are numerical, are the most used: their results are precise but they consume a lot of time and resources. Qualitative methods are based on a symbolic interpretation of the models, and can be used without knowing all the numerical parameters, by relying on dependency relationships between variables. They are less precise but they can be applied very early in the design phase and can be used to plan numerical simulations according to the objectives and to improve the results of analyzes (proofs, optimization, etc.). The work already carried out at the LIDEO laboratory of CEA LIST on modeling and qualitative simulation will be extended by the integration of concepts from naive physics and common sense reasoning to lead to an approach closer to engineering concepts. The results will be used for modeling, simulation but also for optimization on case studies representative of industrial examples.

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Exploring learning techniques for "Edge AI" taking advantage of Resistive RAM

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Systèmes-sur-puce et Technologies Avancées

01-09-2021

SL-DRT-21-0825

Francois.RUMMENS@cea.fr

Artificial intelligence & Data intelligence (.pdf)

Today's computer architectures are inefficient in handling the simulation artificial neural networks, hindering their application in power-constrained environments, such as edge computing and the Internet of Thighs. Dedicated hardware implementations of neural networks that combine the advantages of mixed-signal neuromorphic circuits with those of emerging memory technologies have the potential of enabling ultra-low power processing suitable for edge computing. These new circuits and technologies have the potential to endow the system with the ability to learn at the edge. This breakthrough, which is unattainable using conventional approaches, can have many advantages, as it enables adaptation to changing input statistics, reduced network congestion, and increased privacy. However, current approaches often focus on learning algorithms that cannot be reconciled with the non-ideal physical behaviour of resistive memories. This thesis aims at exploring various algorithmic solutions for inference and learning in order to propose neural network architectures more adapted to the reality of the resistive memory technologies developed at LETI.

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Reliability of 3D avalanche photodetectors

Département Composants Silicium (LETI)

Laboratoire de Caractérisation et Test Electrique

01-10-2020

SL-DRT-21-0830

jean.coignus@cea.fr

Photonics, Imaging and displays (.pdf)

STMicroelectronics develops various CMOS-based technologies for imaging. The rise and democratization of image sensors is leading to a diversification of technological uses such as high-resolution imagery and telemetry for domestic and automotive use. One of the challenges is to meet market needs and adapt to the competition by constantly improving the performance and reliability of devices. The objective of this thesis is to study and model the reliability of avalanche photodetectors for single photon detection. The principle of this sensor lies in the ability to measure the transit time between an optical source and the detector, from a few centimeters to several tens of meters while being insensitive to the surrounding light. A matrix made up of thousands of pixels makes it possible to restore a faithful 3D image of the target. To date, first tests show that the detector degrades over time, leading to a loss of sensitivity and degradation of measurement precision. Quantifying these effects and understanding these drifts is absolutely necessary to improve the manufacturing process and develop a predictive model of reliability. The thesis will focus equally between the reliability of a single pixel and the reliability of a pixel matrix, in order to approach product reliability. The candidate will rely on a set of characterization and reliability measurement tools, as well as modeling and simulation tools developed at STMicroelectronics.

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