The National Institute for Research in Digital Science and Technology (Inria), France is inviting applications for students looking for fully Funded PhD scholarships in the fields of advanced Technology, digital science and artificial intelligence. Below we provide you with a list of available positions with a brief description to each one. For further details, click on each link to reach the official page.
1.PhD Position in Signal processing-based on the squared eigenfunctions of the Schrodinger operator. Application to EEG signals
Project description:
The research project focuses on studying the mathematical properties of the Semi-Classical Signal Analysis (SCSA) method. It will be compared to existing techniques like Wavelets and empirical mode decomposition. Quantum properties of the operator will inform new criteria for selecting the semi-classical parameter, which plays a key role in denoising and signal characterization. Numerical analysis will optimize the current SCSA algorithm, with applications to biomedical signals, particularly EEG signals for epileptic seizure detection and monitoring athletes' mental health.
Academic background:
We seek a student with strong background and expertise in signal processing and mathematics.
Knowledge in biomedical signals and learning algorithms is a plus.
Remuneration
1st and 2nd year : 2051€ gross/month
3rd year : 2158€ gross/month
Application Deadline: 2026-09-30
Description:
The main objective in this assignment is to further enhance the high performance computing capabilities of the numerical tools developed in the DIOGENeS software suite.
The recruited engineer will also actively participate in the studies conducted by the Atlantis team members for demonstrating the benefits of these numerical tools through the simulation of realistic and challenging use cases pertaining to various applications of nanoscale light-matter interactions. In particular, the team is now actively collaborating with potential end-users of the DIOGENeS software suite who are raising various modeling issues that need to be addressed prior to simulating such realistic uses cases.
Deadline: 2024-12-31
3.PhD position Building physics-based multilevel surrogate models from neural networks. Application to electromagnetic wave propagation
Description:
In the present PhD project, we propose to study multilevel distributed strategies for fast training of physics-based DNNs for modeling electromagnetic wave propagation in the frequency domain. We will in particular investigate strategies that can accurately and efficiently deal with the simulation of electromagnetic wave interaction with heterogeneous media, and geometrically complex scattering structures. In this context, the ultimate goal of this project is to develop high-performance parametric NN surrogates that will be used as the forward model in inverse design studies. The first step will be to develop novel methodologies, and assess their performance in a simplified two-dimensional case, on a Helmholtz-type PDE. The extension to the more general three-dimensional Maxwell’s equations will be considered in a second step, informed by the results obtained in the Helmholtz case in two space dimensions.
Deadline: 2024-11-30
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