Light Mode
Dark Mode
Menu

Disciplines

Popular Countries

PhD Position | Fully Funded

F/M Deep Neural Network-assisted computational design of highly efficient ultrafast dynamical metasurfaces

Inria, France

3 Years
Duration

€2,100/ Month
Funding

Dec 31, 2024
Application Deadline

April 1, 2024
Starting Date

About

The PhD subject (thèse CIFRE) is a collaboration between SopraSteria (in Nantes) and DiverSE Inria research team (in Rennes). The candidate will be employee of SopraSteria and spend part of the time in SopraSteria and in DiverSE. 

Overview

Theme/Domain : Numerical schemes and simulations
Scientific computing (BAP E)

The present doctoral project is part of a collaborative project between the Atlantis project-team from the Inria Research Center at Université Côte d’Azur and the CNRS-CRHEA laboratory in Sophia Antipolis, France.

Atlantis is  a joint project-team  between Inria and  the Jean-Alexandre Dieudonné Mathematics Laboratory at  Université Côte d’Azur. The team  gathers applied mathematicians and  computational scientists who are collaboratively undertaking  research activities aiming at the design, analysis, development and  application of innovative numerical methods for systems of  partial differential equations (PDEs) modelling nanoscale light-matter interaction problems. In this context, the team is  developing  the   DIOGENeS  [https://diogenes.inria.fr/]  software suite,  which  implements  several Discontinuous  Galerkin  (DG)  type methods tailored to the systems  of time- and frequency-domain Maxwell equations  possibly coupled  to  differential  equations modeling  the behaviour of propagation  media at optical frequencies.  DIOGENeS is a unique  numerical   framework  leveraging   the  capabilities   of  DG techniques  for  the simulation  of  multiscale  problems relevant  to nanophotonics and nanoplasmonics.

The Research Center for Heteroepitaxy and its Applications (CRHEA) is a CNRS research laboratory. The laboratory is structured around the growth of materials by epitaxy, which is at the heart of its activities. These materials are grouped today around the theme of high bandgap semiconductors: gallium nitrides (GaN, InN, AlN and alloys), zinc oxide (ZnO) and silicon carbide (SiC). Graphene, a zero bandgap material, epitaxially grown on SiC, completes this list. Different growth methods are used to synthesize these materials: molecular beam epitaxy (under ultrahigh vacuum) and various vapor phase epitaxies. Structural, optical and electrical analysis activities have been organized around this expertise in epitaxy. The regional technology platform (CRHEATEC) makes it possible to manufacture devices. In terms of applications, the laboratory covers both the field of electronics (High Electron Mobility Transistors, Schottky diodes, tunnel diodes, spintronics, etc.) and that of optoelectronics (light-emitting diodes, lasers, detectors, materials for nonlinear optics, microcavity structures for optical sources, etc.). The laboratory has also embarked on the “nano” path, including both fundamental aspects (nanoscience) and more applied aspects (nanotechnology for electronics or optics). 

About Us

The Inria centre at Université Côte d’Azur includes 37 research teams and 8 support services. The centre’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 regiona 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.

Eligibility and requirements

Level of qualifications required : Graduate degree or equivalent

Skills

Technical skills and level required

  • Sound knowledge of numerical analysis for PDEs
  • Sound knowledge of Machine Learning / Deep Learning with Artificial Neural Networks
  • Basic knowledge of physiscs of electromagnetic wave propagation

Software development skills : Python and Fortran 2003, parallel programming with MPI and OpenMP

Relational skills : team worker (verbal communication, active listening, motivation and commitment)

Other valued appreciated : good level of spoken and written english

EU citizenship is mandatory

Funding

Benefits package

  • 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)

Remuneration

Gross Salary per month: 2100€ gross per month (year 1 & 2) and 2190€ gross per month (year 3)

Contacts

Apply Now

PhD positions in Computer Science and Artificial Intelligence (AI) across Europe

🎓 Explore exciting fully funded PhD positions in Computer Science and Artificial Intelligence across Europe in top universities!

Interesting PhD Positions in Computer Science

View All PhD Positions in Computer Science and AI