All opportunities

Offers : 66

Phase-Change Memory for high density Storage Class Memory applications

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Start date : 1 October 2018

offer n° SL-DRT-18-0691

Nowadays, the need of a data storage infrastructure allowing Big Data processing requires memory devices with improved performance. The objective of this PhD is the development of innovative Phase-Change Memory (PCM) devices to target Storage Class Memory applications (SCM) that require higher programming speed and endurance. To achieve this goal, the phase change material engineering becomes fundamental, in particular exploring new alloys capable of higher crystallization speed and higher stability. The candidate will contribute to the following tasks: development and electrical characterization of PCMs based on innovative materials, also co integrated with new BackEnd selectors developed in LETI, from single device analysis to full matrix statistics; physico-chemical characterization of the different alloys by resistivity measurements, XRD, FTIR, TEM etc.; multi-physical simulations to correlate the device performances with the material properties.

In addition, the student will contribute to industrial projects, and will interact with experts at the international level in the field of the phase change materials.

  • Keywords : Engineering science, Electronics and microelectronics - Optoelectronics, Materials and applications, DCOS, Leti
  • Laboratory : DCOS / Leti
  • CEA code : SL-DRT-18-0691
  • Contact : gabriele.navarro@cea.fr

Study of Reliability and Degradation mechanisms of GaN on Si devices for power applications

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Start date : 1 October 2018

offer n° SL-DRT-18-0438

GaN-on-Si power devices (HEMTs and Schottky Barrier Diodes) have recently emerged as a competitive solution for medium and low power applications (<650V), such as power converters, thanks to a excellent driving current capability and a high breakdown field. First normally-off commercial devices have been released during last two years showing high frequency performance and good electrical parameters stability over the time. This device generation based on a p-GaN gate is though limited in terms of maximum gate voltage to ensure a sufficient long term reliability. The CEA LETI have chosen a different gate architecture, based on a GaN adapted MIS structure, opening the path of a potential long term reliability breakthrough.

The degradation and aging mechanisms of these novels devices are still not well understood and not enough systematically studied. The aim of the PhD is to explore new electrical characterization methods, recently developed for advanced CMOS technologies, to assess the stability of LETI GaN based power devices. Conventional reliability tests such as Bias Temperature Instabilities (BTI AC or DC), Time Dependent Dielectric Breakdown (TDDB) or power devices dedicated lifetime tests will be used to study the degradation mechanisms of our structures. Part of the work will be dedicated to analyze and understand the root cause of the failure mechanisms thanks to Light Emitting or IR Microscopy or MEB observations. Eventually the degradation physics will be modeled through analytical and numerical simulations.

  • Keywords : Engineering science, Electronics and microelectronics - Optoelectronics, DCOS, Leti
  • Laboratory : DCOS / Leti
  • CEA code : SL-DRT-18-0438
  • Contact : william.vandendaele@cea.fr

Spectral unmixing and classification in X-ray hyperspectral imaging

Mail Sélection

Start date : 1 October 2018

offer n° SL-DRT-18-0731

As part of its X-ray (RX) imaging developments, LETI is studying the contribution of new CdTe-based hyperspectral RX detectors combined with advanced processing methods. The main applications are medical imaging, scientific instrumentation and control for security. The laboratory works in particular on X-ray detection systems of illicit substances such as explosive materials in air transport.

Current data processing methods for discriminating materials or tissues analyzed from measurements are derived from techniques used with dual energy detectors.

The aim of the thesis is to design advanced unmixing and classification algorithms taking into account all the spectral information provided by the detectors to improve the performances of the systems in terms of false alarm rate and good detection rate. The challenge is to demonstrate that these detectors and their associated data processing make it possible to achieve performances specified by equipment certification authorities. The proposed methods might be inspired by spectral unmixing and classification techniques widely developed in the context of hyperspectral imaging for Earth observation.

The candidate must be specialized in signal processing and show interest in physics and instrumentation.

  • Keywords : Engineering science, Mathematics - Numerical analysis - Simulation, DTBS, Leti
  • Laboratory : DTBS / Leti
  • CEA code : SL-DRT-18-0731
  • Contact : caroline.paulus@cea.fr

Influence of protostellar jets on the formation of stellar clusters

Mail Sélection

Start date : 1 September 2018

offer n° SL-DRF-18-0737

  • Keywords : Corpuscular physics and outer space, Astrophysics, FMNT, LTM
  • Laboratory : FMNT / LTM
  • CEA code : SL-DRF-18-0737
  • Contact : patrick.hennebelle@cea.fr

Infrared hyperspectral imaging for the label-free identification of pathogens on agar media

Mail Sélection

Start date : 1 October 2018

offer n° SL-DRT-18-0724

A current challenge in diagnostic microbiology is to develop automation, so as to enhance early diagnosis and preventive medicine. Among the identification methods of bacterial pathogens, optical methods are of major interest as they are noninvasive, nondestructive and label free. Several actual diagnosis devices display the hyperspectral imaging modalities, combining the visible and near infrared wavelengths. But these short wavelengths are not sufficiently informative: they can discriminate some of the targeted pathogens but they cannot yield an identification down to species. Therefore, this thesis work aims at investigating mid and long infrared wavelengths for the imaging of bacterial colonies growing on agar media. These wavelengths are in connection with the vibrational modes of covalent bonds, so they should bring an insight into the chemical composition of microorganisms, in a faster way than spectroscopy. The various wavelengths of interest will be assessed as a first step, then optical sources and detectors will be evaluated. Finally, image processing and machine learning algorithms will be optimized, so as to infer identification from recorded infrared images.

  • Keywords : Engineering science, Life Sciences, Biotechnologies,nanobiology, Optics - Laser optics - Applied optics, DOPT, Leti
  • Laboratory : DOPT / Leti
  • CEA code : SL-DRT-18-0724
  • Contact : mathieu.dupoy@cea.fr
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