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 The National Institute for Research in Computer Science and Automation (Inria), France.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Deep-based semantic representation of avatars for virtual reality (Inria/InterDigital Ys.ai project)
Inria and InterDigital recently launched the Nemo.ai lab dedicated to research on Artificial Intelligence (AI) for the e-society. Within this collaborative framework, we recently initiated the Ys.ai project which focuses on representation formats for digital avatars and their behavior in a digital and responsive environment, and are looking for several PhDs and post-docs to work on the user representation within the future metaverse. This PhD position will focus on exploring, proposing and evaluating novel solutions to represent both body and facial animations with semantic-based approaches for the animation of avatars in a context of multi-user immersive telepresence.
Deadline : 2022-10-31
(02) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Thèse Cifre
Dans le cadre d’un partenariat Inria Safran on envisage un travail de thèse (Cifre) dans le domaine des FANETs ( Flying Adhoc NETworks ) L’objectif est de développer des briques technologiques et des codes de simulation pour ces réseaux .
Deadline : 2022-10-31
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD Thesis – Optimal urban mobility network design for sustainable space sharing between vehicles and soft transport modes
Nowadays, we are witnessing a rapid spread of multimodal mobility in our cities and a willingness on the part of communities to promote new mobility behaviors. These changes are causing road networks to evolve and grow with modifications that are often far from being optimally designed, and public authorities are beginning to investigate how to integrate new paths and roads for the new soft transportation modes (bicycles, e-scooters, etc.). This is a very critical and relevant problem for cities and traffic authorities, which do not have updated nor easy-to-use tools to evaluate the impact of their network design decisions. In practice, several questions remain unanswered such as which road network structure is best suited to support new changes in its capacity, to ease space sharing, and eventually to sustain the replacement of certain roads in favor of soft-mobility dedicated lanes.
Deadline : 2022-10-31
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Video-based dynamic garment representation and synthesis
The Ph.D. position is part of a joint laboratory between Interdigital, a leading technology and research company, and Inria, the French national institute of computer science and automation. In particular, the Ph.D. is shared between an Interdigital team in Rennes, Inria Morpheo team in Grenoble, and Inria Mimetic team in Rennes.
Deadline : 2022-10-30
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(05) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Network economics analysis of energy-aware placement of resources
The European Union is willing to design a trusted, best-in-class European-owned software platform for development, deployment and management of applications across the cloud-to-edge continuum, from central infrastructure to devices. It is important to deal with energy efficiency to reduce (or save) electricity consumption and CO2 emissions to limit global warming. It is typically true due to a massive expected of edge sites submitted to power and heat constraints.
Deadline : 2022-10-15
(06) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Interpretable Deep Learning for image-based species identification
With data-driven AI methods becoming prevalent in more and more aspects of our life, there is a growing effort within the AI community to ensure that these methods do not only perform well, but also communicate to humans some elements of the learned internal reasoning that leads to a particular output. This effort towards Explainable AI (XAI) [1] aims at ensuring that humans can understand the process within the AI model, ultimately allowing for a more human-centric AI. The vast majority of methods, those based on feature attribution, aim at pointing out which parts of the input are most responsible for the output, potentially resulting in an ambiguous interpretation that may end up being misleading [2, 3]. We want to explore how to achieve richer and more useful types of explanations, such as those using prototypical examples [4] or natural language [5], and explore the impact that these explanations have on the users in terms of trust and of how much the users are able to learn from the system. In addition, rich explanations, such as those in the form of visual characteristics in natural language, can be designed to provide an interpretable representation of each data sample that can be leveraged for few-shot and zero-shot learning, as long as the characteristics of new classes are known.
Deadline : 2022-10-12
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(07) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Computer Vision / Deep Learning for human behavior monitoring
Inria, the French National Institute for computer science and applied mathematics, promotes “scientific excellence for technology transfer and society”. Graduates from the world’s top universities, Inria’s 2,700 employees rise to the challenges of digital sciences. With its open, agile model, Inria is able to explore original approaches with its partners in industry and academia and provide an efficient response to the multidisciplinary and application challenges of the digital transformation. Inria is the source of many innovations that add value and create jobs.
Deadline : 2022-10-12
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Explainable Artificial Intelligence for Rule-Based Logical Languages
Deadline : 2022-10-09
(09) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Méthode de simulation numérique pour la propagation d’onde en régime harmonique utilisant sur des fonctions de base micro-localisées
Cette thèse est proposée dans le contexte de l’action exploratoire POPEG (https://www.inria.fr/fr/popeg) financée par Inria. La personne recrutée sera chargée de développer et analyser des méthodes de simulation innovantes pour la propagation d’ondes en régime harmonique. En particulier, l’utilisation de fonctions de base “micro-localisées” comme brique centrale de la méthode numérique est l’originalité principale du sujet proposé.
Deadline : 2022-10-02
(10) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Étude du problème de la réduction de dettes mutuelles entre entreprises
La réduction des dettes mutuelles entre entreprises est un enjeu macroéconomique majeur, tout particulièrement pressant dans les phases descendantes du cycle économique, où les liquidités peuvent manquer à certaines entreprises et conduire à des faillites en chaîne (effet domino). L’idée du projet est de nous intéresser aux réseaux de paiement entre entreprises pour réduire la dette qu’ils contiennent. Nous modélisons le problème par un graphe dont les sommets représentent des entreprises et les arcs représentent des factures émises pendant un laps de temps donné (par exemple un mois). Comme ces factures sont généralement payées avec un certain délai (trois mois en moyenne en zone euro) les dettes qu’elles représentent peuvent être réduites par compensation multilatérale, c’est-à-dire que l’on supprime les dettes communes d’un ensemble d’acteurs et que l’on compense les restes dus à l’aide d’un acteur extérieur. Cela est particulièrement clair dans le cas où ces dettes forment un cycle et mais ces compensations multilatérales peuvent également être appliquées dans le cas de chaînes, de structures arborescentes, etc. Ce système vise donc à diminuer le besoin de liquidités des entreprises et pourrait avoir des effets bénéfiques sur les échanges à l’intérieur d’un groupe d’acteurs économiques fortement reliés. Nous souhaitons concevoir des algorithmes innovants pour réaliser une réduction de dettes mutuelles sur graphes de paiement réels fournis par un opérateur de facturation électronique. Nous disposons de jeux de données qui regroupent plusieurs millions d’échanges réalisés par des entreprises en Italie en 2019 et 2020.
Deadline : 2022-09-30
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(11) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Automated Reasoning for Set Theory
The ANR project BLaSST aims at bridging combinatorial and symbolic techniques in automatic theorem proving, in particular for proof obligations arising from models written in the B formalism. Work will be carried out on SAT-based techniques as well as on more expressive SMT formalisms. In both cases, encoding techniques, optimized resolution techniques, model generation, and lemma suggestion will be considered. Combining both lines of work, the expected scientific impact is a substantially higher degree of automation of solvers for expressive input languages by leveraging higher-order reasoning and enumerative instantiation over finite domains. The effectiveness of the techniques developed in the project will be evaluated by applying them to benchmark sets provided by the industrial partner.
Deadline : 2022-09-30
(12) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD in decision and planning for an autonomous vehicle
This position is part of a very close partnership between Inria and the Valeo group, but also as part of a national collaborative research project of the programme “Plan de Relance de l’Automobile” including the RITS team of Inria and Valeo’s DAR department. The objective is to contribute to the development of algorithms dedicated to the decision and the trajectory planning for autonomous vehicles, operating in road and urban environments. These modules will be validated on real instrumented prototypes belonging to the project partners.
Deadline : 2022-09-30
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(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Compositional verification of system program modules in Rust
Project RIOT-fp [b] is an Inria Challenge with the objective of developing future-proof operating system libraries [1,2,4] for application to IoT: RIOT [a]. Our PhD project is interested in one of the futures of RIOT: RIOT-rs, implemented in Rust [c]. This computing base provides access to a vast ecosystem of analysis, code generation, verification and proof tools [d,e,f]. It offers us to rethink a system software validation process that would suit both system programming and verification requirements (as one may expect from using, e.g., a theorem prover).
Deadline : 2022-09-30
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Formalization of Set Theory and Proof Checking
The ANR project ICSPA aims at improving confidence in the proofs carried out in the context of B, Event-B, and TLA+ by formally and independently verifying these proofs using an independent proof checker with a small trusted base. Moreover, given the similarity between the underlying mathematical theories of these methods, it aims at enabling sharing and reusing proofs and theories between B, Event-B, and TLA+. Both objectives rely on the use of a common logical framework, called the λΠ-calculus modulo theory and implemented in the system Dedukti, in which any formal proof system can be expressed.
Deadline : 2022-09-30
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Trustworthy multi-site privacy-preserving technologies
The overall goal of the TRUMPET project is to research and develop novel privacy enhancement methods for Federated Learning, and to deliver a highly scalable Federated AI service platform for researchers, that will enable AI-powered studies of siloed, multi-site, cross-domain, cross-border European datasets with privacy guarantees that exceed the requirements of GDPR.
Deadline : 2022-09-30
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Intelligent IoT devices management and functionalities virtualization on the edge
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, high mobility and high security level 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 : 2022-09-30
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(17) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Approximation methods for the soundness of control laws derived by machine learning
The design of controllers for large cyber physical systems (CPS, i.e. systems driven both by physical equations and digital controllers) is challenged today by machine learning approaches, and specifically reinforcement learning. The latter however still fail to provide guarantees on the behavior of the controllers it provides. The objective of this thesis is to explore a range of techniques that would make control design for CPS or any other large-scale complex system sound and scalable. The focus will be on quantitative methods, that provide performance guarantees, for example PAC bounds (probably approximately correct).
Deadline : 2022-09-30
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Social and safe navigation of autonomous vehicles in erratic environment
The overall objective of CHROMA is to address fundamental and open issues that lie at the intersection of the emerging research fields called “Human Centered Robotics”, “Multi-Robot Systems” and “AI for humanity”. Their goal is to design algorithms that allow autonomous agents to perceive, decide, learn, and finally adapt to their environment. Their approach for addressing this challenge is to bring together probabilistic methods, machine learning, planning techniques, multi-agent decision making, and constrained optimisation tools. This is done in cooperation with other disciplines such as sociology for the purpose of taking into account human models, or physics to consider self-organized systems. Two main themes are addressed: i) Perception and situation awareness in human-populated environment, by focusing on bayesian perception and sensor fusion, ii) Decision making for single and multi-robot systems
Deadline : 2022-09-30
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Deep interactive control of virtual character’s motion based on separating identity, motion and style (Inria/InterDigital Ys.ai project)
Inria and InterDigital recently launched the Nemo.ai lab dedicated to research on Artificial Intelligence (AI) for the e-society. Within this collaborative framework, we recently initiated the Ys.ai project which focuses on representation formats for digital avatars and their behavior in a digital and responsive environment, and are looking for several PhDs and post-docs to work on the user representation within the future metaverse. This PhD position will focus on exploring, proposing and evaluating novel solutions to represent both body shape and movements in a compact latent representation. This representation aims at simplifying the adaptation of the shape (identity) of a user, or/and his motion, and/or the style of both his shape and motion (such as transferring the user’s moving shape to a fictional character with different properties and style).
Deadline : 2022-09-30
(20) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M HARNESSING LIKELIHOOD-FREE INFERENCE TO LINK DIFFUSION MRI IMAGING WITH CYTOARCHITECTURE CHANGES IN THE MAMMALIAN BRAIN
Sensing microstructural characteristics of human brain tissue with clinical MRI scanners has been an area of heated debate in the diffusion MRI (dMRI) community [1]–[3]. We have recently presented evidence that, if we focus on the cortex, specifically in the insula and anterior cingulate cortex (ACC), the unique characteristics of the cellular populations in these gyri allow us to use clinical-grade scanners to sense the presence of Von Economo neurons (VENs) and link their presence to cognitive function [4]. VENs, uniquely localized in the insula and ACC, are large neurons and their particular size is what enables their quantification through dMRI. However, the inverse problem relating microstructural characteristics to microstructural configurations is plagued by indeterminacies [5]. Furthermore, required dMRI imaging protocols to invert such models are extremely demanding in terms of acquisition time and gradient strength. These combined difficulties point to a lack of computational tools to expand microstructural studies on the mammalian cortex to a wider variety of neuronal populations and cortical areas.
Deadline : 2022-09-22
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M HARNESSING LIKELIHOOD-FREE INFERENCE TO LINK DIFFUSION MRI IMAGING WITH CYTOARCHITECTURE CHANGES IN THE MAMMALIAN BRAIN
Sensing microstructural characteristics of human brain tissue with clinical MRI scanners has been an area of heated debate in the diffusion MRI (dMRI) community [1]–[3]. We have recently presented evidence that, if we focus on the cortex, specifically in the insula and anterior cingulate cortex (ACC), the unique characteristics of the cellular populations in these gyri allow us to use clinical-grade scanners to sense the presence of Von Economo neurons (VENs) and link their presence to cognitive function [4]. VENs, uniquely localized in the insula and ACC, are large neurons and their particular size is what enables their quantification through dMRI. However, the inverse problem relating microstructural characteristics to microstructural configurations is plagued by indeterminacies [5]. Furthermore, required dMRI imaging protocols to invert such models are extremely demanding in terms of acquisition time and gradient strength. These combined difficulties point to a lack of computational tools to expand microstructural studies on the mammalian cortex to a wider variety of neuronal populations and cortical areas.
Deadline : 2022-09-22
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M “Haptic Feedback for Supporting Social Interactions in Virtual Worlds”
The Inria Rennes – Bretagne Atlantique Centre is one of Inria’s eight centres and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.
Deadline : 2022-09-21
(23) 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 : 2022-09-20
(24) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Generative Models for Neural Rendering
This Ph.D. will investigate generative models for neural rendering in computer graphics, both for captured and synthetic scenes. Recent work has seen an explosion in neural rendering techniques based on Neural Fields; however, these methods tend to overfit a single scene [1], making any kind of modification or manipulation very hard. Recent results combining Neural Field Rendering and GANs [2] show a promising avenue of research where the power and expressivity of each can be combined to allow the creation of Neural Representations that are easily to modify and manipulate. We will build on initial results developed in the context of the ERC FUNGRAPH, starting with stochastic structures for 3D textures, then specializing towards more complex categories of scenes (e.g., cars, or specific categories of indoor rooms). Our first results that build on approaches similar to [2] are very promising, both for real and synthetic data; however manipulating real data in a disentangled manner is still very challenging. We will focus on effective training strategies, in the spirit of our previous work (see https://project.inria.fr/fungraph/publications/), possibly combining synthetic or multi-view data with “data in the wild” typically used for GANs, on different ways to extract the generative Neural Field models so they can become usable first-class 3D assets and on novel approaches to editing and manipulating these generative Neural Fields.
Deadline : 2022-09-19
(25) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M 3-year PhD position in Computational Models of Lexical Semantic Change
We invite applications for a 3-year PhD position at the University of Lille in relation to the recently funded research project “COMANCHE” (Computational Models of Lexical Meaning and Change). The position is funded by Inria, the French national research institute in Computer Science and Applied Mathematics. The position is affiliated with the MAGNET team at Inria, Lille, but will also benefit from collaborations with STIH (Sorbonne Université, Paris) and with ATILF (Université de Lorraine, Nancy).
Deadline : 2022-09-15
(26) 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 : 2022-09-13
(27) 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 : 2022-09-01
(28) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Rethinking statistical methods with Flags spaces
This PhD proposal is part of the ERC G-Statistics advance grant # 786854 (2018-2023) from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program..
Deadline : Open until filled
(29) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Adjoint-based error quantification and mesh adaptation for turbulent flows
Numerical simulation has been booming over the last thirty years, thanks to increasingly powerful numerical methods, computer-aided design (CAD), the mesh generation for complex 3D geometries, and the coming of supercomputers (HPC). The discipline is now mature and has become an integral part of design in science and engineering applications. This new status has led scientists and engineers to consider numerical simulation of problems with ever increasing geometrical and physical complexities. A simple observation of this chart
Deadline : 2022-08-31
(30) 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 : 2022-08-31
(31) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Linux as a micro-kernel
In order to facilitate the integration of new schedulers in production-grade operating systems, two main approaches have been proposed: user-defined kernel-level schedulers and user-defined user-level schedulers. In the first case, the scheduling policy is injected (as a plug-in) into the operating-system kernel. In the second case, the custom scheduler runs in user mode (like an application) and interacts with the kernel to leverage its internal mechanisms (e.g., context switching) – only the scheduling policy is delegated to user space. The second approach offers the following benefits: (1) leveraging conventional debugging tools, (2) easily replacing the current scheduling policy (with a simple process launch/restart), (3) using a high-level programming language for the development of the scheduler code. A first step in the latter direction is ghOSt, from Google and Stanford. uFS, from the University of Wisconsin, similarly runs the file system in user space.
Deadline : 2022-08-31
(32) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Cubical models are cofreely generated
La personne recrutée sera amenée à terminer la rédaction sa thèse. Pour une meilleure connaissance du sujet de recherche proposé : Un état de l’art, une bibliographie, des références scientifiques sont disponibles à l’URL suivante, n’hésitez à pas à vous y connecter : (merci de préciser ici le lien vers votre site d’équipe ou tout autre document que vous souhaitez porter à la connaissance du candidat).
Deadline : 2022-08-31
(33) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
Deep Neural Networks (DNNs) [1] are currently one of the most intensively and widely used predictive models in the field of machine learning. DNNs have proven to give very good results for many complex tasks and applications, such as object recognition in images/videos, natural language processing, satellite image recognition, robotics, aerospace, smart healthcare, and autonomous driving. Nowadays, there is intense activity in designing custom Artificial Intelligence (AI) hardware accelerators to support the energy-hungry data movement, speed of computation, and memory resources that DNNs require to realize their full potential [2]. Furthermore, there is an incentive to migrate AI from the cloud into the edge devices, i.e., Internet-of-Things (IoTs) devices, in order to address data confidentiality issues and bandwidth limitations, given the ever- increasing internet-connected IoTs, and also to alleviate the communication latency, especially for real-time safety-critical decisions, e.g., in autonomous driving.
Deadline : 2022-08-31
(34) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Management of mutable data over P2P storage
In this Ph.D. thesis, we plan to propose a replication mechanism over sharded encrypted data that merges concurrent changes and that optimizes the cost of this merging by a suitable replica placement. We propose using CRDTs (Conflict-free Replicated Data Types) [2, 3] as replication mechanism as they are suitable for end-to-end encryption in a peer-to-peer environment where data will be decrypted only at the receiver side and conflicts can be resolved locally. There is therefore no need to decrypt data during data transmission as it is the case for centralised architectures where servers require un-encrypted data in order to perform merging. The challenge in this approach is to develop CRDTs on sharded data stored on IPFS.
Deadline : 2022-08-31
(35) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Visually-assisted Speech Enhancement
In this PhD project, we are going to bridge the gap between the supervised and unsupervised AVSE approaches, benefiting from the best of both worlds. The central task of this project is to design and implement a unified AVSE framework having the following features: 1- Robustness to visual noise, 2- Good generalization to unseen noise environments, and 3- Computational efficiency at test time. To achieve the first objective, various techniques will be investigated, including probabilistic switching (gating) mechanisms [3], face frontalization [4], and data augmentation [5]. The main idea is to adaptively lower bound the performance by that of audio-only speech enhancement when the visual modality is not reliable. To accomplish the second objective, we will explore efficient noise modeling frameworks inspired by unsupervised AVSE, e.g. by adaptively switching to different noise models during speech enhancement. Finally, concerning the third objective, lightweight inference methods, as well as efficient generative models, e.g. with Transformers [6], will be developed. We will work with the AVSpeech [7] and TCD-TIMIT [8] audio-visual speech corpora.
Deadline : 2022-08-31
(36) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Access control for P2P without central authority
This PhD thesis will be in the context of a collaboration between HIVE and Coast and Wide Inria teams. The Ph.D student will be located at Inria Nancy-Grand Est and will be visiting Wide team at Inria Center of the University of Rennes and the Hive offices in Cannes.
Deadline : 2022-08-31
(37) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Quantum control of a mechanical oscillator coupled to a quantum superconducting circuit
This PhD position is in the framework of the “MecaFlux” collaborative project with Sorbonne Université. The experiment is being developed in their group, with the aim to achieve unprecedented control precision, at the quantum level, of a mechanical oscillator. This PhD is meant to analyze the dynamics of this system coupled to superconducting circuits in view of its stabilization and control. A more prospective part of the work could look into particular phenomena which should be observable on such system, among which quantum gravity effects as announced in the project outline.
Deadline : 2022-08-31
(38) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Exploring Human-AI Collaboration and Explainability for Sustainable ML
The 3-year doctoral position is funded by a European Union’s Horizon 2020 grant for SustainML: Application Aware, Life-Cycle Oriented Model-Hardware Co-Design Framework for Sustainable, Energy Efficient ML Systems. The chosen candidate will be supervised by Prof. Wendy Mackay and Dr. Janin Koch. The work will be in close collaboration with the DFKI (German Institute of Artificial Intelligence) and other partners.
Deadline : 2022-08-31
(39) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Using haptic cues to improve micro-gesture interaction
As part of the ANR MIC project, the Ph.D. candidate will work on interaction techniques with micro-gestures. Micro-gestures are hand gestures performed on one hand with the same hand. Examples include tap and swipe gestures performed by one finger on another finger. The Ph.D. thesis aims at improving micro-gesture interaction by leveraging haptic feedback and guidance. The research goal is to design, implement and evaluate interaction techniques based on the innovative combination of micro-gesture and haptic cues for different tasks, starting with pointing and command selection. Later, the candidate will work on specific tasks in an AR/VR environment, emerging from the developed applications in the MIC project, possibly the positioning, rotation, and scaling of 3D objects, as well as text entry. These interaction techniques leverage the sensorimotor loop to foster fast, incremental, reversible, and discoverable interaction.
Deadline : 2022-08-31
(40) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Byzantine fault tolerance and novel Sybil techniques for P2P storage
This PhD thesis will be in the context of a collaboration between HIVE and Wide 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 : 2022-08-31
(41) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Membership Inference Attack in Machine Learning
In this thesis, our plan is to first implement and benchmark typical membership inference attacks proposed in the literature [LZ21, SDS+19, SSSS17, CCTCP21, CCN+22]. We need to carefully outline the impact of crucial parameters such as the hardness of the classification task (dimension of the inputs, number of classes), the size (depth, number of parameters), the training procedure (data augmentation), and the potential overfitting of the target model. This also includes the working assumptions about the attacker’s knowledge on the training data and his computation power. Indeed, some attacks rely on unrealistic assumptions. Designing more tractable attacks is key in order to clearly define when membership attacks are a real threat in practice.
Deadline : 2022-08-31
(42) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Self-supervised learning for implicit shape reconstruction
Recent years have seen a surge in implicit neural shape representations for modeling 3D objects and scenes within deep learning frameworks. Thanks to their ability to continuously represent detailed shapes with arbitrary topologies in a memory-efficient way, these representations alleviate many of the shortcomings of the traditional alternatives such as polygon meshes, point clouds and voxel grids. In practice, these shape functions are typically multi-layer perceptrons mapping 3D points to occupancy or signed distance values. The zero level set of the inferred field can be rendered differentiably through variants of ray marching and tessellated into explicit meshes with Marching Cubes. Coupling these implicit neural functions with conditioning mechanisms allows generalization across multiple shapes. For instance, combining their inputs with local features generated from additional encoding networks [1,2,3,4] yields single forward pass inference models that can learn 3D reconstruction from various input modalities such as images [5,6] or partial point clouds [1,2,3,4].
Deadline : 2022-08-31
(43) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Measuring and Eliminating Bias in Machine Learning Algorithms with Multi-armed Bandits
This position is related to our participation to the Regalia pilot-project (https://www.inria.fr/en/regalia-pilot-project-regulation-algorithms) regarding the regulation of algorithms.
The goal of this Ph.D. is to develop theoretical contributions within this framework, while being able to interact with the real-world through the Regalia project, and, assuming this is relevant, test the proposed solutions.
Deadline : 2022-08-31
(44) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Bandit algorithm for early-stage clinical trials in vaccinology
Advised by Emilie Kaufmann, the recruited PhD candidate will tackle a research project on clinical trials. The goal of this project is to propose new adaptive designs for ealy-stage clinical trials, especially in the context of vaccinology, by leveraging tools from the multi-armed bandit literature. The PhD will be co-advised by Laura Richert in Inria Bordeaux team SISTM, who is an epidemiologist and is involved in the Data Monitoring Board of several clinical trials, for example related to the developpement of VIH vaccines. One of the challenge of the field is that the efficacy of a vaccine can be measured by monitoring multiple indicators of the immune response (e.g. the concentration of different kind of antibodies), which frames the problem of finding an appropriate vaccination strategy as a complex multi-dimensional optimization problem.
Deadline : 2022-08-31
(45) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Distributed Machine Learning in Ubiquitous Environments using Location-dependent Models
The proposed Ph.D. will take place within the Fed-Malin Inria Challenge project. Fed-Malin aims to address the methodological challenges of moving ML operations from the comfortable cloud nest to the wild Internet. Most existing research considers the “Google/Apple setting” with a large set of relatively homogeneous smartphones and the cloud. By contrast, we will consider various scenarios, including entities with significant computation resources (e.g., companies, hospitals), edge servers deployed by telecommunications operators, and (potentially heterogeneous) IoT devices with or without AI edge accelerators.
Deadline : 2022-08-29
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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