Centres Inria associés

Type de contrat

CDD/Fixed-term contract

Contexte

The position is with the Atlantis project-team at the Inria center of Université Côte d'Azur center, focusing on developing numerical modeling tools for nanophotonics. The team is also developing the DIOGENeS software suite for simulating nanoscale light-matter interactions [https://diogenes.inria.fr/].

Mission confié

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The main objective in this assignment is to participate in the develoment 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. 
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Principales activités

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Design and implement computational methods in object-oriented Fortran for partial differential equation models of nanophotonics
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Enhance the DIOGENeS software suite through new features, debugging, and performance optimization
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Collaborate with academic and industrial partners on research projects
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Represent the team at workshops, conferences, and dissemination events
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Develop and maintain technical documentation
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Contribute to scientific publications and technical reports
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Compétences

Required qualifications:
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PhD or Master’s in applied mathematics, scientific computing, computational wave physics, or photonics
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Strong programming expertise in C++ and/or Fortran for scientific computing
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Solid background in numerical analysis and finite element methods
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Familiarity with software engineering practices and version control (e.g., Git)
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Excellent command of English (spoken and written)
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Preferred skills:
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Extensive experience in C++ or Fortran, particularly for high-performance scientific computing
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Proficiency in computational electromagnetics and Maxwell solvers
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Working knowledge of parallel computing (MPI, OpenMP, OpenACC, or CUDA)
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Desired skills:
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Understanding of optimization algorithms
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Experience with reduced-order modeling techniques
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Exposure to deep learning and neural networks
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Proficiency in Python for scientific workflows
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Prior involvement in collaborative or interdisciplinary research projects
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Référence

2025-09212

Thème

Numerical schemes and simulations

Domaine d'activité

Scientific computing