35 Postdoctoral Fellowship at Inria, France

The present postdoctoral project is part of a collaborative project between the Atlantis project-team from the Inria Research Center at Université Côte d’Azur,  (2) Thales R&T in Palaiseau, France, which is the main multidisciplinary research center of Thales group, and one of the main world players in professional electronics (3) and Nanoe in Ballainvilliers, France, whcih is  a SME (Small and Medium Entreprise) specialized  in development and fabrication of innovative ceramic materials for the industries.

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 project will explore quantum protocols based on the concept of quantum nonlocality and quantum networks (see arXiv:2104.10700). A non-exhaustive list of potential projects is:

• Methods for characterizing quantum correlations beyond the Bell scenario:
  • mathematical foundation of these methods (C* algebras, noncommutative polynomial optimization): see e.g. arXiv:2210.09065, arXiv:2212.11299, arXiv:2301.12513
  • improve/find new algorithms for characterizing these correlations
  • numerical developpement of these algorithms, see e.g. arXiv:2211.04483
• Understanding the foundational implications of quantum correlations in networks, see e.g. arXiv:2101.10873 and arXiv:2105.09381
• Develop the applications of network nonlocality to certification protocols, such as
  • randomness generation: arXiv:2209.09921 
  • self testing of measurements and states: arXiv:1807.04956, arXiv:2201.05032
• Adapt existing protocols for their experimental implementation
• Develop practical benchmarks of the concept of ‘Genuine Multipartite Nonlocality’ introduced in arXiv:2105.09381
• Develop SDP relaxations for condensed matter problems, see e.g. arXiv:2212.03014, arXiv:2310.05844, arXiv:2311.18707, arXiv:2311.18706 
• Explore the limits of quantum distributed computing, see e.g. arXiv:1810.10838, arXiv:0903.113

Any other suggested research project in quantum information theory can be discussed (both from the physics, the computer science or the mathematical viewpoint).

This postdoctoral position is part of the national PEPR (Programme et Equipement Prioritaire de Recherche) PlantAgroEco project, coordinated by Alexis Joly. The PEPR involves several teams from various institutes (Inria ZENITH, CIRAD AMAP,  CIRAD PHIM, CIRAD PBVMT, INRAE ePhytia, INRAE IGEPP, INRAE LISAH, IRD EGCE, IRD IEES, Univ. Paris Saclay, TelaBotanica).  This is a postdoctoral position in Machine Learning, more specifically in Reinforcement Learning. We are seeking a highly motivated and skilled postdoctoral fellow to join the project, dedicated to advancing the field of Machine Learning, with a specific focus on Reinforcement Learning. The position is initially funded for 18-month, but it can be easily extended.

 

The starting date is flexible, and ideally would start on Feb. 1st, 2024, but it can be earlier or later. The candidate will be based at Inria Lille – Nord Europe under the expert guidance of Odalric-Ambrym Maillard.

The post-holder will be a member of the DataShape team, and work under the supervision of Nina Otter. 

DataShape is a research team in Topological Data Analysis (TDA), constituted of researchers from Inria-Saclay, Inria Sophia Antipolis, and from the Laboratoire de Mathématiques d’Orsay. TDA is a recent field whose aim is to uncover, understand and exploit the topological and geometric structure underlying complex and possibly high-dimensional data. The DataShape team gathers a unique variety of expertise that allows it to embrace the mathematical, statistical, algorithmic and applied aspects of the field in a common framework ranging from fundamental theoretical studies to experimental research and software development.

The position is in the framework of dAIEDGE—A network of excellence for distributed, trustworthy, efficient and scalable AI at the Edge—funded by the European Union.

The vision of the dAIEDGE Network of Excellence is to strengthen and support the development of the dynamic European edge AI ecosystem under the umbrella of the European AI Lighthouse and to sustain the advanced research and innovation of distributed AI at the edge as essential digital, enabling, and emerging technology in an extensive range of industrial sectors.

The goal of the project is to generalize shallow aquifer models designed for some identified and well-monitored sites, to a whole region. It will be done under the assumption that their hydraulic and geochemical properties are correlated to their fundamental geologic characteristics, and especially their lithology.

This postdoctoral position is part of the national PEPR (Programme et Equipement Prioritaire de Recherche) 5G NF-FITNESS project, coordinated by Daniel Koman, IMT. The PEPR involves several teams from various institutes (CEA, IMT, INRIA, Eurecom, CNRS, Centrale Supelec, INP Toulouse, Nantes Université, ESIEE Paris-UGE). The position is funded for 18 months, and will be conducted at Inria Lille – Nord Europe under the supervision of Nathalie Mitton (Inria) and Patrick Sondi (IMT Nord Europe). This is a postdoctoral position in Vehicle-to-Everything (V2X) communications, more specifically in security and audit of V2X communications.

The project is part of the ERC Starting Grant of Jakob Ruess (Lifeware team at Inria Saclay). Inria is the French national institute for research in computer science, control, and applied mathematics promoting scientific excellence and technology transfer. Within this project, we primarily work on the development of mathematical modeling approaches and statistical inference/estimation methods but we also collaborate with biologists to apply our methods to real data. Our main long-term goal is to develop a comprehensive methodological framework supporting the development of a quantitative understanding of biochemical processes inside single cells that are coupled to the dynamics of growing cell populations. Our research topics are at the intersection of mathematical biology, statistics, control engineering, and statistical physics applied to problems in biology.

This job announcement is for a 2-year postdoc position on the project but we are generally looking for young scientists at all career stages (internship, PhD, postdoc) to join the team at any time in 2024.

The ArticuLabo research group at Inria Paris is seeking a highly motivated postdoctoral researcher to join a multidisciplinary team developing an exciting and ambitious research program at the intersection of social neuroscience and artificial intelligence. Specificially we are developing ways to use hyperscanning techniques to better understand how children in middle childhood use language and nonverbal behavior to build and manage social relationships with peers. The results inform the design of innovative embodied conversational agents (ECAs) capable of helping children learn. 

Recently, an ever-growing number of neuroimaging studies have shown that specific brain areas, such as the temporo-parietal junction, superior temporal sulcus, and pre-frontal cortex show evidence of synchronization (i.e., inter-brain or neural synchrony) in people who are engaged in joint social interactions This observation results from the use of hyperscanning, a technique that allows the simultaneous recording of several brains

As part of the ANR OVOPAUSE project (ANR-22-CE45-0017), the objective is to develop a model for the automatic detection and classification of ovarian follicles, based on 2D histological sections in mice and 3D imaging from clearing tissue in fish. Ovarian follicles are multi-cellular structures that contain female germ cells. The maturation of the follicles goes through successive growth stages until, for some of them, ovulation or laying and the release of the mature oocyte. The distribution of follicles in the different stages of maturity, during life, determines the reproductive state of individuals and certain fertility disorders are associated with a disturbed distribution. The counting of ovarian follicles, and their classification, is therefore a major challenge both for research in reproductive biology and in clinical applications.

Manual counting of ovarian follicles remains an extremely tedious task and has led to the recent development of artificial intelligence approaches. However, to date, no method is fully satisfactory and a global improvement in automatic follicle classification and counting is awaited in this field.

 

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Post-Doctoral Research Visit F/M Structure preserving and multidimensional well balanced discretizations for conservation laws

Deadline : 2024-03-15

View details & Apply

 

This postdoctoral position is part of the national PEPR (Programme et Equipement Prioritaire de Recherche) PlantAgroEco project, coordinated by Alexis Joly. The PEPR involves several teams from various institutes (Inria ZENITH, CIRAD AMAP,  CIRAD PHIM, CIRAD PBVMT, INRAE ePhytia, INRAE IGEPP, INRAE LISAH, IRD EGCE, IRD IEES, Univ. Paris Saclay, TelaBotanica). The position is funded for 18 months, and will be conducted a Inria Lille – Nord Europe under the supervision of Odalric-Ambrym Maillard. This is a postdoctoral position in Machine Learning, more specifically in Reinforcement Learning.

Le centre de recherche Inria Saclay – Île-de-France, créé en 2008, accueille 450 scientifiques et 60 membres des services d’appui à la recherche. Les scientifiques sont organisés en 28 équipes de recherche dont 23 sont communes avec des partenaires du plateau de Saclay.

Le centre Inria Saclay – Île-de-France est un acteur essentiel de la recherche en sciences du numérique sur le plateau de Saclay. Il porte les valeurs et les projets qui font l’originalité d’Inria dans le paysage de la recherche : l’excellence scientifique, le transfert technologique, les partenariats pluridisciplinaires avec des établissements aux compétences complémentaires aux nôtres, afin de maximiser l’impact scientifique, économique et sociétal d’Inria.

The Centre Inria de l’Université de Grenoble groups together almost 600 people in 22 research teams and 7 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE, …), but also with key economic players in the area.

The Centre Inria de l’Université Grenoble Alpe is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

This Post-doc subject is proposed in the context of the ROAD-AI Challenge involving the Cerema and the Inria Team ACENTAURI. ACENTAURI is a robotic team located in Sophia Antipolis that studies and develop intelligent, autonomous and mobile robots that collaborate between them to achieve challenging tasks in dynamic environments. The team tackle perception, decision and control problems for multi-robot collaboration by proposing an original hybrid model-driven/data driven approach to artificial intelligence and by studying efficient algorithms. The team focus on robotic applications like environment monitoring and transportation of people and goods. In these applications, several robots will share multi-sensor information eventually coming from infrastructure. The effectiveness of the proposed approaches are demonstrated on real robotic systems like cars AGVs and UAVs together with industrial partners. Non Destructive Evaluation of Structures and Materials (ENDSUM), directed by Cyrille FAUCHARD, has for main objective to contribute to the development of tools and methods of characterization and diagnosis with great efficiency, less invasive than the current tools and not altering the environments auscultated to meet the challenges of Asset Management of Infrastructures (IPM). The research carried out is aimed first of all at the physical and geometric characterization of environments using a multi-parameter, multi-scale and multi-physical approach linking the quantities measured to indicators useful for the diagnosis and monitoring over time of the environments observed. ENDSUM also aims at the development of analytical and numerical modeling, inversion and data processing and analysis methods (signals, images) allowing access to the desired physical and geometric properties. Finally, ENDSUM aims to develop innovative prototype software and hardware as well as tools for training, research and expertise.

The team expertise encompasses mathematical (stochastic) and numerical modelling of ocean flows, observational and physical oceanography, data assimilation and machine learning. Gathering this large panel of skills, the team aims at improving our understanding, reconstruction and forecasting of ocean dynamics, and more specifically to bridge model-driven and observation-driven paradigms to develop and learn novel representations of the coupled ocean-atmosphere dynamics ocean models. The postdoctoral researcher will work with Noé Lahaye (Inria, Rennes), but close collaborations with other members of the team, in particular with Aurélien Ponte (Ifremer), are expected. The postdoc will be based either at Inria (Rennes, France) or at Ifremer (Brest, France) — as he/she pleases.

The postdoc position is funded by the French National Research Agency (ANR JCJC), as part of the ModITO project (Modelling the Internal Tide in the Ocean)

IsoGeometric Analysis (IGA) offers a powerful framework for the numerical analysis of complex geometric structures, but it comes with significant challenges, particularly in the development of analysis-suitable shape representations. This position aims at the development of novel spline constructions for isogeometric analysis in two and three dimensions. The candidate will work on the definition and implementation of geometrically continuous splines over unstructured meshes. The goal is to obtain accurate description of complex shapes and smooth representations that are suitable for both modeling and analysis.
The universal models shall be applied to modeling and model reconstruction as well as in the numerical resolution of partial differential equations.

Le centre Inria de l’Université de Lille, créé en 2008, emploie 360 personnes dont 305 scientifiques répartis dans 15 équipes de recherche. Reconnu pour sa forte implication dans le développement socio-économique de la région Hauts-De-France, le centre Inria de l’Université de Lille poursuit une relation étroite avec les grandes entreprises et les PME. En favorisant les synergies entre chercheurs et industriels, Inria participe au transfert de compétences et d’expertises dans le domaine des technologies numériques et donne accès au meilleur de la recherche européenne et internationale au profit de l’innovation et des entreprises, notamment dans la région.

The candidate will be hired within the SITAR project (Impact of Information Structures on Service Pricing), funded by the call for project STaRS of the Hauts-de-France région. The candidate will be integrated within the INOCS team, at Inria Lille-Nord Europe. The offer is defined on a 12 months basis, but can be extended up to 18 months. The candidate will be encouraged to take part in international collaborations with the University of Athens and/or with Polytechnic Montréal. The goal of this post-doc is to propose new methods and algorithms to price services targeted at end users, in context of competition where the information available might be limited due to privacy constraints imposed by the end users, or strategic.

The job environment is the one of the Exama project from the NUMPEX programme (see below). We will collaborate with Strabsourg University (See in particular the CEMOSIS center – Center for Modeling and Simulation) on the first workpackage (“Discretization”) relating to geometry processing and scalable mesh generation, based on the CGAL library. NUMPEX software building blocks for future exascale machines. The Numpex programme’s objectives are to design and develop the software building blocks required to equip future ‘exascale machines’ and to prepare the major application domains that aim to fully exploit the capabilities of such machines for scientific research and industry alike. This project is part of France’s response to the next EuroHPC call for expressions of interest (Projet Exascale France) in hosting one of the two major exascale machines planned in Europe for 2024. Numpex will contribute to the creation of a set of tools, software, applications and training which will enable France to remain one of the leaders in the field of international competition through its national Exascale ecosystem that is in step with European strategy.

Inria Défense&Sécurité (Inria D&S) a été créé en 2020 pour fédérer, de façon la plus lisible et opérationnelle possible, les différentes actions d’Inria pouvant répondre aux besoins numériques des forces armées et forces de l’intérieur. L’ambition affichée par Inria est de produire de la recherche ainsi qu’un ensemble de technologies scientifiquement fondées, susceptibles d’être utilisées pour répondre aux défis imminents de la sphère Sécurité Défense.

Inria D&S souhaite développer ses activités de recherche autour du traitement automatique du langage pour des cas d’usage répondant spécifiquement aux besoins dans le domaine Défense&Sécurité. Ces recherches sont menées à travers des collaborations avec le Ministère des Armées et portent sur différentes facettes du domaine comme la transcription de la parole, la traduction automatique, la détection d’entités nommées, la détection de deepfake et l’anonymisation/certification d’origine de la parole ou, encore, la reconnaissance du locuteur et de la langue parlée.

Inria Défense&Sécurité (Inria D&S) a été créé en 2020 pour fédérer, de façon la plus lisible et opérationnelle possible, les différentes actions d’Inria pouvant répondre aux besoins numériques des forces armées et forces de l’intérieur. L’ambition affichée par Inria est de produire de la recherche ainsi qu’un ensemble de technologies scientifiquement fondées, susceptibles d’être utilisées pour répondre aux défis imminents de la sphère Sécurité Défense. Inria D&S souhaite développer ses activités de recherche autour du traitement automatique du langage pour des cas d’usage répondant spécifiquement aux besoins dans le domaine Défense&Sécurité. Ces recherches sont menées à travers des collaborations avec le Ministère des Armées et portent sur différentes facettes du domaine comme la transcription de la parole, la traduction automatique, la détection d’entités nommées, la détection de deepfake et l’anonymisation/certification d’origine de la parole ou, encore, la reconnaissance du locuteur et de la langue parlée.

Inria Défense&Sécurité (Inria D&S) a été créé en 2020 pour fédérer, de façon la plus lisible et opérationnelle possible, les différentes actions d’Inria pouvant répondre aux besoins numériques des forces armées et forces de l’intérieur. L’ambition affichée par Inria est de produire de la recherche ainsi qu’un ensemble de technologies scientifiquement fondées, susceptibles d’être utilisées pour répondre aux défis imminents de la sphère Sécurité Défense.

Inria D&S souhaite développer ses activités de recherche autour du traitement automatique du langage pour des cas d’usage répondant spécifiquement aux besoins dans le domaine Défense&Sécurité. Ces recherches sont menées à travers des collaborations avec le Ministère des Armées et portent sur différentes facettes du domaine comme la transcription de la parole, la traduction automatique, la détection d’entités nommées, la détection de deepfake et l’anonymisation/certification d’origine de la parole ou, encore, la reconnaissance du locuteur et de la langue parlée.

Inria Défense&Sécurité (Inria D&S) a été créé en 2020 pour fédérer, de façon la plus lisible et opérationnelle possible, les différentes actions d’Inria pouvant répondre aux besoins numériques des forces armées et forces de l’intérieur. L’ambition affichée par Inria est de produire de la recherche ainsi qu’un ensemble de technologies scientifiquement fondées, susceptibles d’être utilisées pour répondre aux défis imminents de la sphère Sécurité Défense.

Le postdoctorant travaillera au centre Inria de l’Universté de Lorraine, plus précisément dans l’équipe Mocqua du LORIA. Le postdoctorat se déroule dans le cadre du projet PEPR EPIQ sur le Software quantique, faisant partie du Plan France 2030.  

Automated theorem provers, in particular satisfiability-modulo-theory (SMT) solvers, are increasingly used in industrial contexts. However, these tools are very complex pieces of software, making it hard to ensure that their implementation is correct, and thus, that their output is of any use. A solution to this is to let the prover produce
proof certificates that can be checked by small, independently developed checkers. SMT solvers such as CVC5 are now able to output such certificates in several formats. However, checking such proofs leads to a problem of scaling: these certificates can be very big, and the current tools used to verify them are overwhelmed by such sizes.

This 16 month postdoctoral position is part of the ANR project EngFlea (“Engram of fast learning in the striatum”, https://anr.fr/Project-ANR-21-CE16-0022). It is a collaboration project between the experimental neuroscience lab of Laurent Venance, in Paris (https://www.college-de-france.fr/fr/dynamic-and-pathophysiology-of-neuronal-networks), and Inria project-team AIstroSight, in Lyon (https://team.inria.fr/aistrosight/).  The current position will be located in Lyon within project-team AIstroSight, but borad band interaction with L. Venance lab is expected, including frequent visits to his lab.