Inria, France invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at Inria, France.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Apprentissage pour la prédiction du rang pour des matrices hiérarchique
Dans le contexte de la simulation de la propagation d’ondes electromanétiques, acoustiques et de calcul d’aéroacoustique, des techniques d’approximation par éléments frontières (BEM) sont couramment utilisées. Ces approches conduisent à la résolution de systèmes linéaires denses de très grande taille pour lesquels il serait impossible de former la matrice complète. Des techniques d’approximation de rang faible de certains des blocs peuvent être utilisées qui conduisent à la définition de matrices hiérachiques (H-matrix).
Deadline : 2023-09-30
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Big Data and Machine Learning Methods for Direct-to-Satellite Internet of Things
The doctoral program will occur within the Inria Agora research group at the La Doua Campus in Lyon. The Space-Terrestrial Integrated Internet of Things (STEREO) ANR project (Projet de recherche collaborative- entreprise, or PRCE) (ANR-22-CE25-0014-01 managed by Inria) provides and funds the position. The candidate will collaborate with four group members: Dr. Hervé Rivano (director), Dr. Juan Fraire (encadrant), Dr. Oana Iova, and Prof. Fabrice Valois. Some remote work may be possible. The Ph.D. candidate will utilize pre-existing software tools, including simulators and optimizers provided by the Agora group. There is no requirement for regular travel associated with this position.
Deadline : 2023-08-31
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Trustworthy AI hardware architectures
Context and background: Nowadays, there is a growing and irreversible need to distribute Artificial Intelligence (AI) applications from the cloud to edge devices, where computation is largely or completely performed on distributed Internet of Things (IoT) devices. This trend aims to address issues related to data privacy, bandwidth limitations, power consumption reduction and low latency requirements, especially for real-time, mission- and safety-critical applications (e.g., in autonomous driving, support for gesture and medical diagnosis, smart power grid or preventive maintenance).
Deadline : 2023-08-31
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Energy efficient data management: Data reduction and protection meet performance and energy
This PhD will be hosted by Inria (Myriads team, Rennes Bretagne Atlantique) and will be funded by Inria. This sub-project is a part of the Inria-OVH collaborative framework. Thus, the work will be carried out in a close collaboration with OVH. In fact, we plan to validate the results of the project using several OVH data services including backup services and media service, etc.
Deadline : 2023-08-20
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Modeling brain structural and functional connectivity in neurodegenerative diseases
The neurodegenerative diseases like Alzheimer’s (AD) and Parkinson’s (PD) disease are the consequences of pathological processes that begin decades before the onset of the typical clinical symptoms [1][2]. However, current diagnosis comes quite late in the course of the disease, while evidences underline the multiple benefits that would be associated with earlier diagnosis [3]. An outstanding challenge for clinical neurosciences is therefore to provide reliable, non-invasive, affordable and easy-to-track biomarkers able to improve both the early detection and the monitoring of neurodegenerative diseases, that can be applied at an individual level. It is well acknowledged that AD and PD display a progressive multifactorial disruption of cerebral networks, all along the course of the diseases, which is highly related to the clinical phenotype [4].
Deadline : 2023-07-31
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(06) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Markerless 3D localization of surgical tool in a per-operative context
Today, according to Global Market Insights, the orthopedic medical device (MD) market is growing rapidly and will be worth more than $22.4 billion by 2025. Joint replacement (hip, knee, extremities) represents nearly 37% of the market share. These devices include conventional ancillary instruments, custom-made guides, navigation systems, and robotic systems. More recently, augmented reality (AR) navigation systems have been developed. They are recognized for their accuracy, low cost, ease of use, as well as clinical added value. It is in this context that the ANR MARSurg project [2021-2025] aims to implement an innovative surgical navigation solution with high scientific, technological and clinical potentials.
Deadline : 2023-06-30
(07) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Towards an efficient economic orchestration of 5G and beyond networks
The evolution to a network with multiple players offering connectivity and resources across access, edge and core networks from multiple business partners introduces challenging issues about the relations between those actors and the implications on the overall operations of the network. This study is driven by technological propositions, that impact business models and interactions. A typical example is network slicing, aimed at supporting services with heterogeneous constraints, that is also an opportunity for Network Operators (NOs) to get more value out of the transport of services by being part of the content distribution value chain. Network slicing is also seen as one of the most important building blocks for network automation, as it brings more agility in the management of services. Here, an economic model needs to be associated with the technological innovation and its behavior studied in an orchestrated network.
Deadline : 2023-06-30
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Socially-Aware Embodied Conversational Agents: Achieving Task and Social Goals in Human-Computer Conversation with students
The objective of this project is to build embodied conversational agents (also known as ECAs, or virtual humans, or chatbots, or multimodal dialogue systems) that have the ability to engage their users in both social and task talk, where the social talk serves to improve task performance. In order to achieve this objective, we model human-human conversation, and integrate the models into ECAs, and then evaluate their performance. This position is a 3-4 year doctoral contract.
Deadline : 2023-06-30
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(09) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Nonlinear observer design using AI tools
The conventional problem of bearings-only target motion analysis (BOTMA) is studied in the project. It assumes that the two mobile agents, monitor and target, are on the same plane and that they (or at least target) have a constant speed during the observation time period. The goal is to estimate the position of a target, namely two coordinates of geographical location and the projections of the speed on two axes, from a set of available perturbed bearing measurements collected by the monitor.
Deadline : 2023-06-30
(10) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Stochastic methods for uncertainty modelling and quantification in coupled physical-biogeochemical ocean models
Numerical modelling of marine ecosystems is an essential component of the simulation systems currently being developed to perform multi-decadal projections of the state of the oceans under anthropogenic pressures. The models used must integrate a representation of the couplings between physical and biogeochemical processes that act on a wide range of spatio-temporal scales and that constrain the dynamics of upper trophic levels and fisheries resources.
Deadline : 2023-06-30
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(11) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Frugal control of robots
In the current time of major, global ecological crisis, robots could help us satisfy more efficiently our most basic needs (food, health, clothing, housing, transport), but to do so, they should reduce their own ecological footprint, considering the energy and overall resources necessary to manufacture and operate them. One overlooked aspect in this regard is the design and implementation of control laws, which can lead to intensive computations and impact the whole hardware design of robots.
Deadline : 2023-06-30
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(12) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Algorithmique des Isogénies de Variétés Abéliennes et Cryptographie Post-Quantique
La cryptographie basée sur les isogénies a connu un développement rapide durant ces dernières années, sous l’impulsion de l’invention en 2011 de SIDH [10], un système d’échange de clé basé sur les isogénies de courbes elliptiques supersingulières. Ce cryptosystème et ses variantes ont connu un fort engouement, notamment dû au fait qu’il promettait de résister aux attaques utilisant un ordinateur quantique. Malheureusement, des travaux récents ont permis de mettre en oeuvre des attaques dévastatrices sur SIDH, le rendant de fait obsolète [3,13]. Toutefois, le mouvement créé par SIDH a permis le développement d’une boîte à outils algorithmique diversifiée pour les isogénies de courbes elliptiques et a conduit également à la découverte d’autres constructions cryptographiques telles que CSIDH [5], SQISign [7], CSI-FiSh [2], etc.
Deadline : 2023-06-30
(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Trust-based approaches in multi-technology Industrial Internet of Things (M/F)
The Inria FUN research group investigates solutions to enhance programmability, adaptability and reachability of FUN (Future Ubiquitous Networks) composed of RFID, wireless sensor and robot networks. Limited resources, and high mobility evolving in distrusted environments characterize the objects that compose FUN. They communicate in a wireless way. To be operational and efficient, such networks have to follow some self-organizing rules. Indeed, components of FUN have to be able in a distributed and energy-efficient way to discover the network, self-deploy, communicate, self- structure in spite of their hardware constraints while adapting the environment in which adapting the environment in which they evolve. For additional information on the FUN research group, please see http://team.inria.fr/fun/
Deadline : 2023-06-26
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Automated Reasoning for Set Theory
The application of the B method is supported by Atelier B, maintained by the Clearsy company, a platform that contains several engines for automatic proof. In a recent experiment, among the roughly 77,000 proof obligations of a representative industrial development project, 64% were proved automatically, leaving 28,000 obligations to be proved by human interaction. Also, no significant feedback is provided in case an obligation cannot be proved. Given recent advances in automated theorem proving, we believe that the number of proof obligations that can be discharged automatically can be improved significantly, and that tools can help users by explaining why certain obligations cannot be proved.
Deadline :2023-06-23
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Inverse Control of Erosion Simulation
The Ph.D. is part of the ANR JCJC project INVTERRA, which seeks to model physically plausible and editable terrains for computer graphics environments. The thesis will handle the main scientific challenges of the project: the definition of the erosion processes, their neural representation, and the inversion of control parameters. The project will be led in collaboration with other research groups with expertise in terrain or geology and will include travels for visits or conferences.
Deadline : 2023-06-23
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Inference of causal models for networks from single observations
The work will take place at Inria Univ. Grenoble Alpes, Montbonnot, France either with frequent travels to Nokia Bell Labs, Massy, France.
Deadline : 2023-06-19
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(17) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Audio-visual Speech Enhancement: Bridging the Gap between Supervised & Unsupervised Approaches
This is a fully-funded PhD position as part of the REAVISE project: “Robust and Efficient Deep Learning-based Audio-visual Speech Enhancement” (2023-2026). REAVISE aims to develop a unified audio-visual speech enhancement (AVSE) framework that robustly integrates acoustic data (noisy speech signal) with accompanying visual information (video of speaker’s lip movements) in order to recover an intelligible, high-quality estimate of the clean speech signal with low computational power and independently of the acoustic and visual noise environments. These objectives will be achieved by leveraging the recent methodological breakthroughs in statistical signal processing, machine learning, computer vision, and deep neural networks.
Deadline : 2023-06-18
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Alternative approaches for privacy-preserving in federated learning
Federated learning (FL) enables a large number of IoT devices (mobiles, sensors) to cooperatively to learn a global machine learning model while keeping the devices’ data locally [MMR+17, LSTS20]. For example, Google has applied FL in their application Gboard to predict the next word the users would type on their smartphones [HRM+18]. FL can help to mitigate privacy concerns, as the raw data is kept locally by the users and never needs to be sent elsewhere. However, maintaining the data locally does not provide itself formal privacy guarantees.
Deadline : 2023-06-18
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Automated medical image segmentation
Inria, a French research institute dedicated to digital sciences, employs 2,600 people from the best universities in the world, and takes up the challenges of computer science and mathematics. Inria has 9 centers in France, including the Inria Grenoble research center, which employs nearly 730 people. Inria is organized into “project teams” which bring together researchers with complementary skills around a focused scientific project.
Deadline : 2023-06-17
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(20) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Reliable and cost-efficient data placement and repair in P2P storage over immutable data
This PhD thesis will be in the context of a collaboration between HIVE and Myriads and Coast Inria teams. The Ph.D student will be located at Inria Center of the University of Rennes and will be visiting team Coast at Inria Nancy-Grand Est and the Hive offices in Cannes.
Deadline : 2023-06-16
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Optimal Control and Machine Learning for Quantum Computing Systems
Deadline : 2023-06-16
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Inexact optimization for the control of robots
The control of complex robots is commonly computed by numerically solving optimization problems [1,2]. These problems are often small enough (from tens to a few thousand variables) that they can be solved exactly, or with the highest numerical precision available. It would be beneficial, however, to study what precision is really needed at the different computation steps: formulation of the problem, accuracy of the solution or inner computations of the optimization. This could help perform cheaper computations, allowing faster resolution and better energy efficiency.
Deadline : 2023-06-15
(23) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Leveraging Vehicular Computing to Increase Edge and Cloud computation Capabilities
A powerful approach to enhance mobile applications’ performance is enabling mobile devices to offload some of their computational-intensive workloads to the remote servers at the Edge or the Cloud. A considerable literature exists on offloading tasks on static edge servers [MKB18][KLC19][OZC18][DLQS18]. More recently, a new idea of offloading tasks to vehicles is emerging, such as in [ALEGE17][AOW+12]. But unfortunately, vehicles are assumed to be static. More recent work tackles the more challenging dynamic and stochastic case of moving vehicles [SGS+19], where offloading can only occur on vehicles. In [ZZD15][SHC+18], consider a joint allocation strategy considering both vehicles, Edge and Cloud. However, in the former, a task is offloaded to vehicles only if it fails to be offloaded to the Edge or the Cloud. Other works explore the multi-hop capabilithttps://www.resultadda.in/wp-admin/ies of vehicular networks to allow remote nodes to access the Edge and offload their tasks [DCL20][HL20][HLW20]. We believe that the vehicles can play an essential role in absorbing the computing load on the Edge or the Cloud by allowing resource allocation closer to users with a significant reduction in energy costs for the Edge and delays.
Deadline : 2023-06-15
(24) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Massively Multi-User Wireless Communications
Wireless connected devices such as smartphones, computers and TVs, autonomous cars, watches, sensors, lightbulbs and numerous sensors proliferate as our lifestyle becomes increasingly intertwined with digital services. From the point of view of communications networks, these devices give rise to a new class of data traffic, more sporadic, and for some applications requiring more stringent reliability guarantees than what classical mobile broadband can offer. In particular, the mechanisms and protocols classically used to mitigate transmission collision between randomly activated transmitters are not efficient in the new regime of many users and small payloads. A significant breakthrough was made with the introduction of the unsourced random access paradigm [P17]; one of the proposed approaches is based on the use of multi-linear spreading as a modulation, which allows convenient user separation at the receiver using tensor algebraic considerations [DLG21]. The object of the proposed study is to develop modulations and waveforms for massive multi-user wireless communications that can be applied to a wide class of propagation channels, including multipath and time-varying channels, and support asynchronous or quasi-synchronous operation.
Deadline : 2023-06-11
(25) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Unsupervised Machine Learning for Wireless Communications
Wireless communication systems involve collecting large amounts of data related to electromagnetic propagation, which is normally used for the purpose of data transmission and demodulation, and then immediately discarded. While it is clear that leveraging the statistical aspects of propagation information (e.g. through learning the characteristics of its distribution and applying appropriate statistical techniques) has the potential to greatly enhance the performance and range of services offered by the network, this approach faces the practical challenges of real-time processing such as a limited computing and storage resources.
Deadline : 2023-06-11
(26) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Understanding and addressing within-user variability in active Brain-Computer Interfaces
Brain computer interfaces (BCI) are communication and control tools that enable their users to interact with computers by using brain activity alone, typically measured using electroencephalography (EEG). A prominent type of BCI is active BCI (aBCI), that translates change in brain activity due to mental imagery tasks performed by the user (e.g., imagination of movements or mental calculation) into control commands for a computer. Such aBCIs are very promising for various applications, e.g., for post-stroke rehabilitation, hand-free control or assistive technologies for motor impaired users. However, current aBCIs are rather unreliable, and their reliability degrades even more when used across contexts (e.g., across days, for changing users’ states or applications used) due to various sources of variabilities. Unfortunately, such variabilities are 1) often ignored in the literature, as most BCIs are assessed in a single context and 2) poorly understood. Thus, for BCIs to fulfill their promises and be used outside laboratories, we need to make them robust to such variabilities. In ANR (French National Research Agency) project PROTEUS (2023-2026) we propose to do so by 1) Systematically measuring BCI and brain signal variabilities across various contexts while sharing the collected databases; 2) Characterizing, understanding and modeling the variability and their sources based on these new databases; and 3) Tackling these variabilities by designing new machine learning algorithms optimally invariant to them according to our models, and using the resulting BCIs for two practical applications affected by variabilities: tetraplegic aBCI user training and auditory attention monitoring (passive BCI) at home or in flight. The present PhD project aims at understanding and addressing these variabilities for aBCIs in particular.
Deadline : 2023-06-11
(27) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD – Alternative algorithms for the simulation of lattice models
Deadline : 2023-06-10
(28) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Effective algebraic invariants for multi-parameter persistence
Topological Data Analysis (TDA) is among the recent trends in exploratory data analysis, and it has aroused a steadily growing interest within the last two decades. Its main contribution has been to provide new types of data descriptors that encode information about the topology of data.These descriptors are of an essentially different nature compared to classical descriptors encoding geometric or statistical quantities.
Deadline : 2023-06-05
(29) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Learning host-pathogen surface interactome to design novel therapeutics
The main goal of this PhD project is to study the surface interactome of an important human-specific pathogen in interaction with human/mouse plasma to elucidate the protein-protein interactions that help the bacteria to evade the immune responses. Such information will be used then to design protein binders to inhibit such interactions. To achieve this goal, the candidate will develop a deep learning model to predict the binding sites and the potential binders within the search space. This position will provide international collaboration with microbiologists and protein design groups with the possibility of in-site internships for 1-3 months.
Deadline : 2023-06-04
(30) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Experimental evaluation of sliced cellular networks
The overall objective of the DIANA project-team is to design, implement and evaluate advanced networking architectures. To do so, the team works to provide service transparency and programmable network deployments in the context of both wired and next generation wireless cellular networks. The team’s methodology includes advanced measurement techniques, design and implementation of architectural solutions, and their validation in adequate experimental facilities. The DIANA team designed, deployed and operates R2lab, a wireless testbed designed with reproducibility as its central characteristics. The team collaborates with Eurecom to deploy and operate an open programmable platform to test post-5G services. Recently, the team enriched R2lab with 5G professional radio units and compute resources managed by Kubernetes clusters to provide an experimental cloud-native environment to test with open source (OAI, SrsLTE) software and some commercially licensed software (e.g. Amarisoft) for 5G/6G networks supporting for example scenarios with disaggregated 5G networks elements. Other recent contributions of the team include: Enhanced Transport-Layer Mechanisms for Multi-Access Edge Computing-Assisted Cellular Networks, Bencharmking Mobile Networks from the Viewpoint of Video Streaming QoE, Introducing Fidelity in Network Emulation, and Enhanced Ray Tracing Techniques for Accurate Estimation of Signal Power.
Deadline :2023-06-04
(31) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Monitoring Plane for mobile cellular networks
The overall objective of the DIANA project-team is to design, implement and evaluate advanced networking architectures. To do so, the team works to provide service transparency and programmable network deployments in the context of both wired and next generation wireless cellular networks. The team’s methodology includes advanced measurement techniques, design and implementation of architectural solutions, and their validation in adequate experimental facilities. The DIANA team designed, deployed and operates R2lab, a wireless testbed designed with reproducibility as its central characteristics. The team collaborates with Eurecom to deploy and operate an open programmable platform to test post-5G services. Recently, the team enriched R2lab with 5G professional radio units and compute resources managed by Kubernetes clusters to provide an experimental cloud-native environment to test with open source (OAI, SrsLTE) software and some commercially licensed software (e.g. Amarisoft) for 5G/6G networks supporting for example scenarios with disaggregated 5G networks elements. Other recent contributions of the team include: Enhanced Transport-Layer Mechanisms for Multi-Access Edge Computing-Assisted Cellular Networks, Bencharmking Mobile Networks from the Viewpoint of Video Streaming QoE, Introducing Fidelity in Network Emulation, and Enhanced Ray Tracing Techniques for Accurate Estimation of Signal Power.
Deadline : 2023-06-04
(32) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Non-smooth modelling of the interaction between granular flows and obstacles in complex 3D geometries
The PhD project aims at developing a non-smooth modelling of granular flows down an incline disturbed by singularities in complex geometries in three dimensions. This modelling aims to investigate in detail the coupling between the mean hydrodynamic behaviour of the grains’ assembly in interaction with a structure on the one hand and the discrete nature of the material at stake and the resulting fluctuations on the other hand. An increased complexity will be implemented in the modelling approach not only in terms of the granular material type considered (dry non-cohesive or cohesive) but also in term of the obstacle which disturbs the flow (fixed and rigid structure versus deformable structure). The objective is to achieve a sufficiently realistic simulation of the interaction of shallow granular flows (with a few grains across the thickness) involved in nature, like dense snow avalanches or rockfalls, in interaction with singularities: topographic accidents, fixed and rigid obstacle, deformable structure, etc.
Deadline : 2023-06-01
(33) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Analyse asymptotique des reseaux de neurones par methode de physique statistique
These en co-encadrement par Giulio Biroli, dans le cadre de l’institut Prairie
Deadline : 2023-06-01
(34) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Algorithmique des séquences pour la reconstruction de génomes à partir de données métagénomiques complexes.
La caractérisation des communautés de micro-organismes associées à un environnement, appelées microbiotes, passe généralement par le séquençage de leur ADN dans des études métagénomiques1. Certains environnements sont plus complexes à étudier que d’autres en raison de la grande diversité microbienne qui les compose ; c’est le cas du sol ou encore du microbiote associé aux plantes2. Afin de pouvoir étudier le contenu génomique des espèces, et ainsi inférer leur fonctionnement dans l’environnement, la métagénomique plein-génome est utilisée en routine, générant des lectures dont l’assemblage peut permettre de reconstruire des génomes individuels ou MAGs (metagenome-assembled genomes)3. Cet assemblage se fait encore majoritairement à partir de lectures courtes en utilisant des graphes de de Bruijn4, permettant d’obtenir des séquences plus grandes appelées contigs. Il est très souvent complété par une étape de clustering visant à grouper les contigs qui proviennent d’une même espèce (binning), notamment en utilisant des critères de fréquence tétra-nucléotidique et d’abondance des contigs, afin de former les MAGs.
Deadline : 2023-06-01
(35) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Trustworthy multi-site privacy-preserving technologies
While AI techniques are becoming ever more powerful, there is a growing concern about potential risks and abuses. As a result, there has been an increasing interest in research directions such as privacy-preserving machine learning, explainable machine learning, fairness and data protection legislation.
Deadline : 2023-05-31
(36) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Stochastic modelling of communications networks
PhD part of the ERC NEMO project
Deadline : 2023-05-31
(37) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Optimization of resources placement in Fog-based IoT systems based on latency analysis
The Fog computing is a recent paradigm that address such issues by provisioning resources outside the cloud and closer to the end-device, at the edge of the network. This allows to reduce the latency and minimize the traffic between end-user and the cloud plat-form [3]. Several studies have shown that fog systems can indeed reduce the latency compared to cloud systems, but this reduction is not guaranteed and will highly depend on the components placement, leading sometimes to worse performance [8]. It has been also demonstrated that less traffic is sent to the cloud when using fog systems. However, a lack of a proper monitoring or reconfiguration mechanism in the fog exists, especially when the application is related to the IoT [7], where the cloud infrastructure is known not to be a viable solution.
Deadline : 2023-05-31
(38) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Tracing business rules in source code
This thesis is part of a joint research team between the software publisher Berger-Levrault and the RMod team at the CRIStAL laboratory and the Inria Lille Nord Europe research center. The two partners have been working together for several years. A first joint thesis was defended in October 2021 and two others are in progress.
Deadline : 2023-05-31
(39) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Théorie des bandits pour le suivi personnalisé de patients.
Le projet BIP-UP financé par l’ANR débute le 1er janvier 2023 et durera 4 années. BIP-UP s’appuie sur une collaboration existant depuis plusieurs années entre l’équipe Inria Scool, dirigée par Philippe Preux et l’unité INSERM 1190 localisée au CHU de Lille, dirigée par François Pattou, tous deux professeurs à l’Université de Lille.
Deadline : 2023-05-31
(40) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Remote attestation for Internet-of-Things swarms
This PhD position is in the context of the Horizon Europe project OpenSwarm, a 40-month research and innovation project coordinated by INRIA Paris and funded by the European Commission. The project aims at developing novel systems of collaborative smart nodes able to interpret the data they generate, and to collaborate in a decentralized manner to communicate efficiently, even in the context of mobility. The technology developed will be validated through 5 use cases in different environments, like agriculture, industry and maritime transport. The project gathers 8 other partners, prestigious universities and industrials in Europe.
Deadline : 2023-05-31
(41) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Télé-opération de robots à la troisième personne
Équipe LARSEN / Inria Nancy – Grand Est : https://team.inria.fr/larsen
Deadline : 2023-05-31
(42) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Evaluating stereotyped biases in auto-regressive language models
Sémagramme, INRIA Nancy Grand-Est, https://team.inria.fr/semagramme/
Deadline : 2023-05-31
(43) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD Position / Generating distributed programs from formal specifications
VeriDis, Inria Nancy Grand-Est, https://team.inria.fr/veridis/
Deadline : 2023-05-31
(44) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Elucidating conformational dynamics of protein-RNA complexes
The main goal of this PhD project is to elucidate the conformational dynamics of protein-RNA complexes and to develop a method for understanding their allosteric communications. To achieve this objective, the candidate will develop a deep learning model to predict communication pathways. They will investigate several facets of the algorithms and ultimately provide this application to the broad scientific community. The proposed deep learning model will be set up to address the characterization of dynamic properties of protein-RNA interactions at the 3D level. This approach is a prerequisite for the design of new therapeutics that target protein-RNA complexes.
Deadline : 2023-05-31
(45) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Méthodes géométriques pour des problèmes d’ondes en milieux hétérogènes
Dans cette thèse on se propose d’étudier la discrétisation et la construction de modèles réduits pour des problèmes de type d’onde en milieu hétérogène à l’aide d’approches basées sur la géométrie symplectique et différentielle.
Deadline : 2023-05-31
(46) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Next-Best-View Planning for 3D Reconstruction with Cooperative Multi-UAV Systems
The selected candidate will join the INRIA Chroma team (https://team.inria.fr/chroma/) at CITI-lab INRIA/INSA Lyon, and work under the supervision of Alessandro Renzaglia and Olivier Simonin. The overall objective of the Chroma group is to address fundamental and open issues that lie at the intersection of “Human-Centered Robotics” and “Multi-Robot Systems”. Our goal is to design algorithms and develop models allowing mobile robots to navigate and operate in complex and dynamic environments. Within this context, an important line of research focuses on online planning for cooperative systems and in particular for fleets of aerial robots. Our approach for addressing this challenge is to bring together probabilistic methods, planning techniques and multi-agent decision models.
Deadline :2023-05-31
(47) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Adversarially Robust Machine Learning-based Network Intrusion Detection System
Within the framework of the ANR PEPR project “Superviz”.
Deadline : 2023-05-31
(48) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H [DOCT2023-KAIROS] Reconnaissance de programmes par réseaux de neurones
Un résultat fondamental en informatique (calculabilité) nous affirme que des problèmes indécidables existent, c’est-à-dire pour lesquels il n’existe aucun algorithme qui soit capable d’en fournir une solution. Cela n’est pas une bonne nouvelle fondamentale, car cela prouve qu’il existe des problèmes de calculs qui ne peuvent pas être résolus par une méthode automatique.
Deadline : 2023-05-31
(49) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Accélération du produit matrice-vecteur par la méthode multipolaire rapide pour des clusters de machines hétérogènes
La méthode multipolaire rapide (fast multipole method, FMM) est une technique mathématique hiérarchique développée pour accélérer le calcul des forces de longue portée dans le problème à N-corps réduisant la complexité de quadratique à linénaire. D’un point de vue algébrique, elle peut être vue comme produit matrice-vecteur (MV) où la matrice est découpée hiérarchiquement en sous-matrices. Contrairement à un calcul complètement algèbrique, les sous-matrices sont traitées analytiquement, via l’expansion de la fonction de Green du système par une expansion multipolaire, le groupement des sources voisines permettant de les traiter comme une source unique.
Deadline : 2023-05-31
(50) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Balancing Performance and Sustainability for FaaS in the Fog
The PhD student will work in the MYRIADS team, part of IRISA and INRIA RENNES – BRETAGNE ATLANTIQUE at Rennes. The team focuses on building next generation utility computing platforms for highly distributed cloud and fog infrastructures (http://www.irisa.fr/myriads). Rennes is the capital city of Brittany, in the western part of France. It is easy to reach thanks to the high–speed train line to Paris. Rennes is a lively city and a major center for higher education and research.
Deadline : 2023-05-31
(51) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M MAIIL – AI-driven character simulation based on Multi-Agents Interaction Imitation Learning
Simulation of autonomous entities capable of collaborating or competing with real humans, as real other humans would in the same situation, is still a scientific and technological challenge. This is especially a complex problem when dealing with fullbody interaction between simulated and real entities, as it involves complex spatiotemporal constraints at different timing scales (continuous motion and sequence of actions), with a high-dimension research space (associated with the characters’ degrees of freedom). Let us consider several characters, real and simulated humans, that have to collaborate to manipulate a digital mockup. Another interesting example is the coordination of (simulated and real) humans to compete against another team. In both cases, the simulated entities should behave to help or compete with real humans, as other real humans would in this situation, in a long-term close collaboration/competition. Hence, the problem is not to find an optimal solution to efficiently achieve the task, but act as expected by the participants, finding suboptimal but realistic solution.
Deadline :2023-05-31
(52) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M 3-year PhD position in Automatic Argumentation Mining in French Legal Decisions
We invite applications for a 3-year PhD position co-funded by Inria, the French national research institute in Computer Science and Applied Mathematics, and LexisNexis France, leader of legal information in France and subsidiary of the RELX Group. The position is affiliated with the MAGNET, a research group at Inria, Lille, which has expertise in Machine Learning and Natural
Language Processing, in particular Discourse Processing. The PhD student will also work in close collaboration with the R&D team at
LexisNexis France, who will provide their expertise in the legal domain and the data they have collected.
Deadline : 2023-05-31
(53) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Leveraging Radiance Fields Rendering for Asymmetric Collaboration in Extended Reality
This PhD proposal is framed under the PePR Ensemble (http://pepr-ensemble.fr/prog_doctoral.html) and will be conducted in collaboration between Inria and IMT-Atlantique. Inria. Two Inria teams, located at different sites (Rennes and Sophia-Antipolis) will be involved in the PhD. The Hybrid team (Dr. Ferran Argelaguet) will ensure the direction of the PhD and bring their expertise in VR, 3D user interfaces and avatars. The Grapheco team (Dr. Geroge Drettakis) is a world leading team in image-based rendering, although not directly involved in the co-supervision on the PhD, will provide support for the fast radiance-field rendering methods.
Deadline : 2023-05-31
(53) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Creating socially reactive virtual characters for enhanced social interactions in Virtual Reality
Creating compelling immersive situations requires to deal with several important elements. Amongst these, simulating and displaying convincing virtual humans naturally interacting with users is crucial to replicate real-life situations and foster collaboration, due to the importance of interpersonal interactions in our everyday life. In the last decade, great advances have been seen in the quality of such virtual characters, such as in terms of appearance (e.g. Metahuman characters) or the ability to control characters in game-like situations (e.g., Motion Matching [But15]). However, when it comes to interactions with users, such virtual characters typically only display limited, and often scripted, behaviours. For instance, virtual pedestrians are typically steered to avoid other characters and users using crowd simulation methods (e.g RVO [VLM08]), but will not react appropriately if users suddenly startle them, intrude their personal space, or act inappropriately.
Deadline : 2023-05-31
About The National Institute for Research in Computer Science and Automation (Inria), France –Official Website
The National Institute for Research in Computer Science and Automation (Inria) is a French national research institution focusing on computer science and applied mathematics. It was created under the name Institut de recherche en informatique et en automatique (IRIA) in 1967 at Rocquencourt near Paris, part of Plan Calcul. Its first site was the historical premises of SHAPE (central command of NATO military forces), which is still used as Inria’s main headquarters. In 1980, IRIA became INRIA. Since 2011, it has been styled Inria.
Inria is a Public Scientific and Technical Research Establishment (EPST) under the double supervision of the French Ministry of National Education, Advanced Instruction and Research and the Ministry of Economy, Finance and Industry.
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