47 Postdoctoral Fellowship at Inria, France

This postdoctoral research is part of the REAVISE project: “Robust and Efficient Deep Learning based Audiovisual Speech Enhancement” (2023-2026) funded by the French National Research Agency (ANR). The general objective of REAVISE is to develop a unified audio-visual speech enhancement (AVSE) framework. This will leverage recent breakthroughs in statistical signal processing, machine learning, and deep neural networks to create a robust and efficient AVSE system.

Assignment – Candidates for postdoctoral positions are recruited after the end of their Ph.D. or after a first post-doctoral period: for the candidates who obtained their PhD in the Northern hemisphere, the date of the Ph.D. defense shall be later than September 1, 2022; in the Southern hemisphere, later than April 1, 2022. In order to encourage mobility, the postdoctoral position must take place in a scientific environment that is truly different from the one of the Ph.D. (and, if applicable, from the position held since the Ph.D.); particular attention is thus paid to French or international candidates who obtained their doctorate abroad.

We are looking to hire a post-doc for 12 months in the area of formal methods at Inria, Université de Rennes.

The research project will be about formal verification and testing of real-time systems using timed automata and techniques from game theory, reinforcement learning, temporal logics, automata learning etc.
More specifically, we will explore reinforcement learning techniques to develop black-box testing algorithms for timed automata.

We require from the candidate to have a strong background on theory of formal verification, a strong publication record, and if possible, experience or interest in implementing formal verification tools.

Dans le cadre d’une collaboration Acumes et l’entreprise Altair, avec un cofinancement AMIES, l’objectif est de développer les schémas de type cut-cell dans le logiciel OpenRadioss, en vue de la simulation de charges creuses et de problèmes d’interaction fluide-structure rapides.

L’entreprise Altair développe le code propriétaire Radioss depuis plus de 30 ans pour l’optimisation et l’évaluation des performances de produits sur des problèmes hautement non-linéaires et soumis à des chargements dynamiques. Depuis septembre 2022, Altair propose une version open-source de Radioss, OpenRadioss, dirigée vers le codéveloppement avec le monde académique et les développeurs externes. Le but est de faciliter le développement et l’intégration de nouvelles fonctionnalités dans le code open-source OpenRadioss, dont les versions stabilisées et validées seraient ensuite intégrées dans le code propriétaire Radioss. Il est également envisagé que ce code pourra fournir un outil de référence aux chercheurs souhaitant développer des applications dans ce domaine. Le code open-source est fourni avec l’environnement d’intégration continue et les fonctionnalités de parallélisation du code propriétaire actuel. Le pré- et post-traitement peut être effectué avec des outils open-source tels que Gmsh et Paraview.

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).

A post-doctoral fellowship is available in the Inria TRiBE team at the Saclay Center. This position is funded in the context of the National French PEPR projects on “Networks of the Future” and “Mobility Digitalization”. The post-doctoral fellow will collaborate with Dr. Aline C. Viana (https://pages.saclay.inria.fr/aline.viana/) and Nadjib Achir (https://nadach.github.io) from the TRiBE team and Razvan Stanica (http://perso.citi.insa-lyon.fr/rstanica/)  from the Inria Agora team.

Candidates for postdoctoral positions are recruited after the end of their Ph.D. or after a first post-doctoral period: for the candidates who obtained their PhD in the Northern hemisphere, the date of the Ph.D. defense shall be later than September 1, 2022; in the Southern hemisphere, later than April 1, 2022. In order to encourage mobility, the postdoctoral position must take place in a scientific environment that is truly different from the one of the Ph.D. (and, if applicable, from the position held since the Ph.D.); particular attention is thus paid to French or international candidates who obtained their doctorate abroad.

Every year Inria International Relations Department has a few postdoctoral positions in order to support Inria international collaborations.

The postdoctoral contract will have a duration of 12 to 24 months. The default start date is November 1st, 2024 and not later than January, 1st 2025. The postdoctoral fellow will be recruited by one of the Inria Centres in France but it is recommended that the time is shared between France and the partner’s country (please note that the postdoctoral fellow has to start his/her contract being in France and that the visits have to respect Inria rules for missions)

 

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Post-Doctoral Research Visit F/M Numerical modeling of acoustic waves in an active Sun

Deadline : 2024-06-30

View details & Apply

 

This project follows the line of long term reserach on the development of improved discretizations for complex PDEs. Here the main focus are hyperbolic balance laws arising in many applications in physics and engineering. More particularly this project looks at so called structure preserving methods which  embed genuinely discrete analogs of continuous constraints. Examples   are  solenoidal constraints and curl involutions, which also include he  enhanced preservation of steady states, often referred to as well balanced. Other constraints as non-negativity or bounded variation  within physically admissible values are also of great importance.

The goal of the project include:

1. The promotion or development of design rules and interoperability standards,

• to ensure the interoperability of collaborative heterogeneous assets
• to support secure sharing of resources and exchange of data and information between those systems and platforms for the benefit of the mission execution and performance in systems of systems contexts
• to offer mission system software scalability to speed up integration of new capabilities
• to contribute to the interoperability of mission system execution platforms

2. To define functional interfaces of sensors the assessment of questions brought by the implementation of AI technologies, including :

• Using trustable AI-based functions
• European autonomy over AI engineering tools, algorithm libraries and methods enabling the use of AI in military assets

• Compatibility of tools and processes for the development, the validation, the qualification and the certification of AI-driven operational services

The position generally requires working on a state-of-the-art analysis of Artificial Intelligence and related technologies in order to identify appropriate tools and libraries for autonomy.

Notre modèle pour le contrôle de ces essaims de micro-nageurs doit intégrer plusieurs aspects physiques cruciaux :

• La complexité du fluide environnant, incluant parfois des vortex turbulents et des parois étroites et rugueuses.
• Les interactions hydrodynamiques entre le fluide et les nageurs.
• Les effets d’interaction, telle que la traînée qu’un nageur impose à ses voisins.
• Potentiellement, les effets de la déformation du nageur sur le fluide environnant.

Pour relever ces défis, notre approche envisage l’utilisation de modèles variés qui prennent en compte ces interactions physiques à divers degrés de complexité. Nous explorerons l’application de techniques avancées d’apprentissage machine, telles que l’apprentissage par renforcement et l’apprentissage profond, pour optimiser la navigation et le contrôle de ces essaims et synchroniser ces ensembles.

The MathNeuro project-team in the Inria branch at the University of Montpellier focuses on understanding brain activity at multiple scales (i.e. from single-cell, microcircuits to large scale brain processes). MathNeuro has a core at the intersection of Mathematics and Neuroscience, but it also employs a multidisciplinary approach combining theory, computational modelling, as well as, data science. In line with this, our collaborations involve experts from diverse fields, including experimentalists, clinicians, and data scientists. The research lines of MathNeuro include questions related to plasticity (both synaptic and non-synaptic) and associated learning rules, memory, excitability, with applications in both normal and pathological brain states, as well as, ageing brain. Recent research portfolios include novel mathematical classification of neuronal bursting, explanation of asynchronous neurotransmitter release (via competition of timescales) and application areas such as, understanding migraine, epileptic seizures, Alzheimer’s Disease (AD) and ageing.

The hired postdoc will join PreMeDICaL, an Inria/Inserm research team based in Montpellier (France), and will be jointly supervised by Aurélien Bellet and Julie Josse. PreMeDICaL specializes in developing precision medicine methods through causal learning and federated learning, while ensuring the confidentiality of medical data. The team is composed of researchers in statistics, machine learning, AI, as well as clinicians, and aims to bridge the gap between fundamental research and its effective use in healthcare. Through his/her research, the hired postdoc will contribute to the research axes “Personalized medicine by integration of different data sources” and “Personalized medicine with privacy and fairness guarantees”.

n the context of the CIIAM project (Contextual Information Inference for Argument Mining), funded through the France 2030 investment plan managed by the National Research Agency (ANR), as part of the Initiative of Excellence Université Côte d’Azur, aiming to enhance the robustness of argument mining techniques through the synthesis of contextual information relevant to multimodal aspects of communication.

We invite doctoral candidates nearing completion of their thesis and young PhD graduates to apply for a postdoctoral position on “Improving Argument Mining through the Synthesis of Contextual Information” (12 months).

This post-doc position fits within the roadmap activities of Inria’s Defense & Security Department, which is devoted to applications-driven research.

Among the various fields of NLP, information extraction is a crossroad topic that, by focusing on how to turn raw documents into structured data models, echoes the practical needs of many end-users in a broad range of sectors. Information extraction components such as entity recognition or relation extraction are thus key to a number of industrial and general-public applications.

However, whereas information extraction has seen major progresses in the last few years on common language (Wikipedia, news, everyday language), it still lags behind on specialty language, which effectively affects a number of practical applications. Main challenges include unknown words and concepts, unusual phrasings, or differences in the nature of information that is interesting to extract.

L’ objectif est du poste est de développer, implémenter, tester et valider des méthodes d’apprentissage statistique qui permettent de modéliser et de prédire la progression de maladies neurodégénératives et la survenue d’évènements.

This postdoc is situated in the context of ANR CREATTIVE3D, a French state-funded project that deploys virtual reality headsets (VR) to study navigation behaviors in complex environments, and the impact of low-vision conditions. It involves partners in computer science and neuroscience from the Université Côte d’Azur (I3S, CHU Nice, LAMHESS) as well as the LPC lab of Aix-Marseille Université. The postdoc project will be entirely carried out in the Biovision team of Inria Center at Université Côte d’Azur.

The postdoc is funded by the project PDE-AI of PEPR IA. The recruited researcher will work with people from McTAO team in Sophia Antipolis and LJAD CNRS math lab in Nice.

L’équipe Inria MIMESIS, basée à Strasbourg, recherche un.e chercheur.se en simulation numérique pour la santé, avec expertise en traitement d’images médicales, mécanique des milieus continus et méthode des éléments finis.

L’équipe Inria MIMESIS est une équipe de recherche de renommée internationale travaillant dans le domaine de l’assistance à la planification et délivrance thérapeutique, au travers d’approches combinant traitement d’image médicale, simulation numérique, machine learning et vision par ordinateur. Le consortium MEDITWIN dont l’équipe MIMESIS fait partie, cherche à développer des jumeaux numériques pour la planification patient-spécifique de la thérapie par ablation thermique de précision pour le traitement locorégional du cancer du foie.

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 deep-fake 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.

La mission s’inscrit dans le cadre de travaux sur la capacité d’adapter diverses applications de traitement automatique de la parole à un nouveau langage, dialecte (ou variante locale).

Cela à faible coût, au sens des ressources d’entrainement, comme la quantité de données brutes, la quantité et/ou le niveau de métadata disponibles (label de langue et transcription, par exemple), au sens de la quantité de calcul et au sens de l’effort humain. Le recours à des solutions innovantes d’entrainement faiblement ou non supervisés et à des solutions intrinsèquement plurilingues sera privilégié. Aux aspects de frugalité déjà évoqués s’ajoute une demande d’explicabilité, apte à renforcer le fonctionnement des solutions développées dans un cadre réel.

Avec l’équipe projet et sous la responsabilité de son porteur, Jean-François Bonastre, vous interviendrez principalement sur deux aspects :

• D’une part, vous participerez à la mise en œuvre d’une solution à l’état de l’art pour l’identification de la langue parlée, avec la plateforme d’évaluation associée, pour constituer un système de référence dans le domaine de la détection de la langue parlée.
• D’autre part, vous travaillerez à renforcer la généricité, la précision et le passage à l’échelle de l’approche BA-LR.

Vous participerez également en soutien dans la valorisation des travaux.

The candidate will work on formal methods for quantum computing within the PEPR project EPIQ.
The aim of the PEPR project EPIQ is to study Quantum Software and develop the quantum stack from quantum algorithms, to models of computation and simulation. This project is part of the Plan France 2030.
We are looking for an excellent and experimented researcher to contribute to quantum programming languages, formal methods and models of quantum computing. The recruited researcher will particularly work on the development of formal methods for quantum control and hybrid frameworks (classical and quantum), with a focus on compilation, resource estimation and resource optimization.
An expertise in quantum programming languages and formal methods is expected to conduct ambitious research activities within the project. Knowledge on graphical languages (quantum circuits, ZX-calculus, … ), semantics, and/or lambda-calculi, is required to contribute and reinforce the expertise of the consortium.

A post-doctoral fellowship is available in the Inria Agora team in the Lyon center. This position is funded in the context of the National French PEPR projects on “Networks of the Future” and “Mobility Digitalization”. The post-doctoral fellow will collaborate with Dr. Razvan Stanica (http://perso.citi.insa-lyon.fr/rstanica/) from the Inria Agora team and with Dr. Aline Viana (https://pages.saclay.inria.fr/aline.viana/) from the Inria TRiBE team.

Inria Agora is a joint team with INSA Lyon, one of the most prestigious engineering schools in France. Teaching involvement and student supervision are possible (but not mandatory) at INSA Lyon.

Recent advances in computational mass spectrometry-based metabolomics have unleashed a massive amount of chemical knowledge from metabolomics analysis. Yet, there is a need for a comprehensive computational framework that can better integrate the information derived from both experimental and computational analyses and help chemists analyse their results.

We invite applications for a Postdoctoral Researcher position at the Nice Chemistry Institute (ICN) and the Wimmics team at Inria both hosted at the Université Côte d’Azur. The selected candidate will be jointly embedded and interact with PhD students and research engineers of the Interdisciplinary Institute for Artificial Intelligence (3iA) TechPool, and operates in the context of international collaboration between France and Switzerland. The position is initially offered for one year, with the possibility of extension up to three years.

The research objective is to advance the foundations of algebraic algorithms, with a specific emphasis on deepening the connections between real algebraic geometry and practical applications. We are particularly interested in applying our findings to the realm of robotics, focusing on the intricacies of design. Our primary area of focus lies in the development of parallel manipulators. This involves delving into various aspects such as direct and inverse kinematics quandaries, path planning complexities, and the nuanced considerations of parameterized designs, including error analysis. Through this endeavor, we aim to contribute to the enhancement of robotic systems and their efficiency in real-world scenarios. At a second level, we opt for the use of such mechanisms for dedicated tasks emanating from problems in control theory.

L’objectif est de récolter des données multi-sources, multi-formats, et de les fusionner dans un système d’information géographiques adapté à la prise en compte des informations pertinentes dans les modèles hydrauliques. Le format de ce SIG sera à déterminer, car si les informations de topographies sont classiquement représentées sous forme d’un modèle numérique de terrain de type raster, il serait intéressant de conserver les formats vectoriels lorsque cela est possible, car ils sont beaucoup moins lourds à gérer.

La mission consistera tout d’abord à récolter des données géographiques de type « shapefile » existantes sur les zones modélisées, que ce soit en milieu urbain ou sur le Mekong, puis d’en extraire les informations utiles au modèle hydraulique.

Every year Inria International Relations Department has a few postdoctoral positions in order to support Inria international collaborations. The postdoctoral contract will have a duration of 12 to 24 months. The default start date is November 1st, 2024 and not later than January, 1st 2025. The postdoctoral fellow will contribute to the CuriousTech team and be recruited by the Inria Centre of the University of Bordeaux in dialog with the University of Waterloo (Canada) (please note that the postdoctoral fellow has to start his/her contract being in France and that the visits have to respect Inria rules for missions). 

This project aims to investigate a new generation of data collection, combining intelligent wireless sensors and aerial means, and test this approach in agriculture in the framework of AgriNet. The main objective is to use unmanned aerial vehicles (commonly called “drone”) as data mules to collect data from connected objects on the ground, in natural environments. This aerial solution will facilitate collections in hard-to-access natural environments, which can also suffer from signal attenuation with traditional communication networks. In this context, drones offer a large geographical zone of intervention, and are easier to deploy than land-based mobile vectors (e.g. ground vehicles). Compared to traditional sensor networks, this approach greatly lightens the hardware infrastructure to deploy, by avoiding the installation of numerous gateways to route information from the sensor nodes; gateways are expensive, energy intensive and require regular maintenance, which is incompatible with their presence in an uneasily accessible natural environment.

Every year Inria International Relations Department has a few postdoctoral positions in order to support Inria international collaborations. A postdoctoral position is opened within the Inria-KAIST partnership. It is part of the SHAARE associate team, initiated between the Auctus team at Inria and the IRiS lab at KAIST that focuses on haptics and shared teleoperation. Together, we aim at developing shared-control approaches that, either, better guide the human through adaptive haptic guidance, or adjust the robot behavior according to the human gestures.

Candidates for postdoctoral positions are recruited after the end of their Ph.D. or after a first post-doctoral period: for the candidates who obtained their PhD in the Northern hemisphere, the date of the Ph.D. defense shall be later than September 1, 2022; in the Southern hemisphere, later than April 1, 2022.

In order to encourage mobility, the postdoctoral position must take place in a scientific environment that is truly different from the one of the Ph.D. (and, if applicable, from the position held since the Ph.D.); particular attention is thus paid to French or international candidates who obtained their doctorate abroad.

The postdoctoral fellow will be recruited by one of the Inria Centres in France but it is recommended that the time is shared between France and the partner’s country (please note that the postdoctoral fellow has to start his/her contract being in France and that the visits have to respect Inria rules for missions)

Candidates for postdoctoral positions are recruited after the end of their Ph.D. or after a first post-doctoral period: for the candidates who obtained their PhD in the Northern hemisphere, the date of the Ph.D. defense shall be later than September 1, 2022; in the Southern hemisphere, later than April 1, 2022.

Every year Inria International Relations Department has a few postdoctoral positions in order to support Inria
international collaborations.
The postdoctoral contract will have a duration of 12 to 24 months. The default start date is November 1st, 2024 and not later than January, 1st 2025. The postdoctoral fellow will be recruited by one of the Inria Centres in France but it is recommended that the time is shared between France and the partner’s country (please note that the postdoctoral fellow has to start his/her contract being in France and that the visits have to respect Inria rules for missions).

Resist team at Inria Nancy and the University of Abomey-Calvi (UAC) have started in 2024 an associate team focusing on the cyber security of Industrial Control Systems. These systems refer to specialized computer systems and networks that manage and control industrial processes. ICS are employed in various industries, including manufacturing, energy production, transportation, etc. They are fundamental in monitoring and regulating industrial processes, ensuring efficiency, safety, and reliability. They include Supervisory Control and Data Acquisition (SCADA) systems, a type of ICS that collects data from sensors remotely and provides a human-machine interface for operators to make real-time decisions. For instance, Benin has initiated projects to modernize the Electrical grid of the ”Société Béninoise d’Energie Electrique (SBEE)”. For this, Benin has built “a National Distribution Control Center (Dispatching)” for the intelligent management of its electrical grid. Indeed, the National Distribution Control Center is a modern infrastructure based on SCADA system allowing real-time monitoring and control of the power distribution network and data collection. This SCADA Electrical grid supervision system enables the analysis of data collected on the Electrical grid to make remote decisions in real time and detect breakdowns to intervene remotely. The smart grid’s optimal and secure data management has become an significant challenge for the Beninese government. This associated team project and the research that will be conducted will be of great help to meet the challenges of securing and analyzing threats of the communication systems widely deployed in such smart grids.

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.

Current research in control theory is focused on utilizing the dynamics of large networks, such as traffic and transportation infrastructure, multi-agent systems, epidemic spreading, and electrification of vehicles, among others. Dealing with a high number of state variables that describe the nodes or edges of these networks, as well as significant uncertainties, calls for new reduction methods that are suitable for networks and can effectively navigate through different scales. Traditionally, the control community has tackled the control of large-scale network systems by seeking distributed control algorithms, where each node applies a control loop locally based on its own information. However, this approach often requires access to local information that may not be available for all nodes in the network. As an alternative to this decentralized approach, the objective of this thesis is to explore “the continuation method” proposed in the ERC Scale-FreeBack project [2,3,4].The continuation method represents a novel approach for approximating large-scale networks described by sets of ordinary differential equations (ODEs) using partial differential equations (PDEs). It is particularly applicable to high-dimensional spatially distributed ODE systems. Examples of such systems include urban traffic networks, ring oscillators, electrical networks, multi-agent robots, gas dynamics, fluid density studies, and electro-mobility networks. In essence, the continuation process can be understood as the inverse of the typical space discretization of PDEs, where a large set of ODEs is used. It begins with a set of coupled or uncoupled high-dimensional ODEs distributed in space, which is then approximated by a PDE using finite differences. Once this approximation is established, boundary controllers can be designed for the PDE instead of controlling each individual control system, or the PDE can be used for analysis purposes [5]. The control designed at the PDE level is subsequently applied to the real system by discretizing it back to the original ODE system.