Internship position F/M Advanced computational design of nanostructured photonic devices
Type de contrat : CDD
Niveau de diplôme exigé : Bac + 5 ou équivalent
Autre diplôme apprécié : Master in applied mathematics or scientific computing
Fonction : Stagiaire de la recherche
A propos du centre ou de la direction fonctionnelle
The Inria center at Université Côte d'Azur includes 42 research teams and 9 support services. The center’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM ...), but also with the regional economic players.
With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d'Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.
Contexte et atouts du poste
Nanophotonics is the science that studies the interactions between light and matter at the nanoscale. Light is an electromagnetic wave whose wavelength is in the visible spectrum, i.e., between approximately 400 nm to 800 nm. In this context, one refers to as sub-wavelength structuring of matter. The structuring of matter at these scales allows these interactions to be shaped for a variety of technological and societal applications. Among the technological applications of nanophotonics are the control of solar energy (nanostructured solar cells for photovoltaic panels, or for photovoltaic devices embedded in intelligent), improving the sensitivity of digital imagers (nanostructured CMOS image sensors for smartphones, tablets and digital cameras), improving the extraction and emission of light in optoelectronic devices (microLED-based displays). Societal applications are in particular concerned with human well-being (nanoparticle-based therapeutic strategies, biosensing for the detection of viruses). Numerical modeling is extensively used for understanding the physical phenomena underlying light-matter interactions, but also for tailoring or harnessing these interactions guided by specific performance objectives. The first objective requires to numerically solve the system of time-domain or frequency-domain Maxwell equations coupled to differential equations modeling the behavior of propagation media at optical frequencies while the seond goal is addressed by leveraghing a numerical optimization algorithm in the framework of an inverse design workflow. For both objectives, the Atlantis team is developing the DIOGENeS [https://diogenes.inria.fr/] software suite, which is dedicated to the numerical study of multiscale problems relevant tonanophotonics and nanoplasmonics. DIOGENeS implements several Discontinuous Galerkin (DG) type methods for which the team has developed a long-term expertise [1-3]. It also includes a includes an inverse design component, which relies on statistical learning-based global optimization methods for single-objectove, multi-objevctive and robust optimization [4-6].
Beside the above-mentioned high-fidelity DG-based electromagnetic solvers, the team is also actively studying reduced-order modeling (ROM) strategies in the context of time-domain electromagnetics by studying the applicability of the proper orthogonal decomposition (POD) method. In this ROM approach, a reduced subspace with a significantly smaller dimension is constructed by a set of POD basis vectors extracted offline from snapshots that are extracted from simulations with a high order DGTD (Discontinuous Galerkin Time-Domain) electromagnetic solver [1-2]. In particular, a non-intrusive POD-based ROM has been developed for the solution of parameterized time-domain electromagnetic scattering problems where considered parameters are the electric permittivity and the temporal variable [7]. Although the non-intrusive POD-based ROM method introduced in [7] provides encouraging results, it is not as efficient and robust as one would expect and it does not allow to account for a parametrized geometry. In particular, the hyperbolic nature of the underlying PDE system, i.e., the system of time-domain Maxwell equations, is known to represent a challenging issue for linear reduction methods such as POD. In practice, a large number of modes is required therefore hampering the obtention of an efficient ROM strategy. Therefore, searching for alternative ROM strategies for nanophotonics remains an active and important line of reserach of teh Atlantis project-team.
[1] J. Viquerat. Simulation of electromagnetic waves propagation in nano-optics with a high-order discontinuous Galerkin time-domain method. Ph.D. thesis, University of Nice-Sophia Antipolis, Dec 2015.
[2] S. Lanteri, C. Scheid and J. Viquerat. Analysis of a generalized dispersive model coupled to a DGTD method with application to nanophotonics. SIAM J. Sci. Comp., Vol. 39, No. 3, pp. A831–A859 (2017)
[3] E. Agullo, L. Giraud, A. Gobé, M. Kuhn, S. Lanteri and L. Moya. High order HDG method and domain decomposition solvers for frequency‐domain electromagnetics. Int. J. Numer. Model. Electr. Netw. Dev. Fields, Vol. 33, No. 2 (2019)
[4] M.M.R. Elsawy, S. Lanteri, R. Duvigneau, G. Brière, M.S. Mohamed and P. Genevet. Global optimization of metasurface designs using statistical learning methods. Scientific Reports, Vol. 9, No. 17918 (2019)
[5] M.M.R. Elsawy, A. Gourdin, M. Binois, R. Duvigneau, D. Felbacq, S. Khadir, P. Genevet and S. Lanteri. Multiobjective statistical learning optimization of RGB metalens. ACS Photonics, Vol. 8, No. 8, pp. 2498–2508 (2021)
[6] M.M.R. Elsawy, M. Binois, R. Duvigneau, S. Lanteri and P. Genevet. Optimization of metasurfaces under geometrical uncertainty using statistical learning. Optics Express, Vol. 29, pp. 29887-29898 (2021)
[7] K. Li, T.-Z. Huang, L. Li and S. Lanteri. Non-intrusive reduced-order modeling of parameterized electromagnetic scattering problems using cubic spline interpolation. J. Sci. Comp., Vol. 87, Art. no. 52 (2021)
Mission confiée
The objective of this internship is twofold:
- One one hand, the existing numerical methodology combining the high-fidelity fullwave DGTD solver [1]-[2] and the statistical learning-based global optmization method [4]-[5] will be used to study different nanostructuring strategies for improving light absorption in a simplified yet representative model of photonic devices relevant to digital imaging technology;
- On the other hand, a detailed assessment of state-of-the-art ROM techniques will be conducted to identify possible paths to extend the approach developed in [7] in view of dealing efficiently with the inverse design of large-scale photonic devices such as a realistic CMOS imager.
This internship work is expected to be a first step toward a PhD project that will be concerned with the development of an advanced computational design methodology for studying and improving the performance of CMOS imagers. This PhD project will be funded a Cifre grant in the framework of a collaboration between the Atlantis project-team of Inria research center at Université Côte d'Azur and STMicrolectronics (CMOS Imagers division of the Technology for Optical Sensors department) in Crolles.
Principales activités
- Getting started with the numerical tools in the DIOGENeS software suite
- Development of different gemetrical models of the model nanostructured photonic device
- Realization of inverse design studies
- Bibliographical study of state-of-the-art ROM techniques
- Publications
Compétences
Technical skills and level required :
- Master or engineering degree in numerical mathematics or scientific computing
- Sound knowledge of numerical analysis and numerical methods for PDEs
- Basic knowledge of physiscs of electromagnetic wave propagation
Software development skills : Python and Fortran 2003
Relational skills : team worker (verbal communication, active listening, motivation and commitment)
Other valued appreciated : good level of spoken and written english
Avantages
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Contribution to mutual insurance (subject to conditions)
Rémunération
Traineeship grant depending on attendance hours.
Informations générales
- Thème/Domaine :
Schémas et simulations numériques
Calcul Scientifique (BAP E) - Ville : Sophia Antipolis
- Centre Inria : Centre Inria d'Université Côte d'Azur
- Date de prise de fonction souhaitée : 2025-03-01
- Durée de contrat : 4 mois
- Date limite pour postuler : 2025-02-28
Attention: Les candidatures doivent être déposées en ligne sur le site Inria. Le traitement des candidatures adressées par d'autres canaux n'est pas garanti.
Consignes pour postuler
Applications must be submitted online on the Inria website. Collecting applications by other channels is not guaranteed.
Sécurité défense :
Ce poste est susceptible d’être affecté dans une zone à régime restrictif (ZRR), telle que définie dans le décret n°2011-1425 relatif à la protection du potentiel scientifique et technique de la nation (PPST). L’autorisation d’accès à une zone est délivrée par le chef d’établissement, après avis ministériel favorable, tel que défini dans l’arrêté du 03 juillet 2012, relatif à la PPST. Un avis ministériel défavorable pour un poste affecté dans une ZRR aurait pour conséquence l’annulation du recrutement.
Politique de recrutement :
Dans le cadre de sa politique diversité, tous les postes Inria sont accessibles aux personnes en situation de handicap.
Contacts
- Équipe Inria : ATLANTIS
-
Recruteur :
Lanteri Stéphane / Stephane.Lanteri@inria.fr
A propos d'Inria
Inria est l’institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l’interface d’autres disciplines. L’institut fait appel à de nombreux talents dans plus d’une quarantaine de métiers différents. 900 personnels d’appui à la recherche et à l’innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'efforce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.