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: PhD Position F/M PhD position – QAT
We are seeking highly motivated and talented students to join our research team and contribute to the advancement of cryptographic verification techniques for delegated quantum computations. This position offers an excellent opportunity to work at the intersection of quantum physics and cryptography, collaborating with leading institutions in the field.
Deadline : 2023-07-22
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Distributed Training of Heterogeneous Architectures
This PhD thesis is in the framework of the Inria-Nokia Bell Labs research initiative on Federated Learning for Cellular Networks and in closer relation with Inria research initiative on Federated Learning, FedMalin https://project.inria.fr/fedmalin/.The PhD candidate will join Nokia Bell Labs research team in Massy, France https://www.bell-labs.com/about/locations/paris-saclay-france/ and will also be a member of the Inria project-team NEO https://team.inria.fr/neo/.The Machine Learning & Systems team, part of the AI Research Lab at Nokia Bell Labs, is composed of computer scientists and data engineers who develop AI-based systems and algorithms bridging the gap between the promise of limitless capabilities of AI and the constraints imposed by real computing and communication systems. NEO is positioned at the intersection of Operations Research and Network Science. By using the tools of Stochastic Operations Research, the team members model situations arising in several application domains, involving networking in one way or the other.
Deadline : 2023-07-23
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Hair Capture and Modeling
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. The PhD will be one of several PhD topics around the avatar representation of people, within a collaboration framework between Inria and InterDigital called Nemo.ai. The PhD will start as soon as possible and will last 3 years. It will be supervised by The Morpheo team at INRIA Grenoble Rhône-Alpes and the MetaVideo group at InterDigital Research and Innovation labs in Rennes. The focus of Morpheo’s research is on perceiving and interpreting moving shapes, with applications to character animation, and immersive and interactive environments. The MetaVideo group that will co-supervise the PhD develops representations for the transmission of digital human and avatar character models in interactive environments.
Deadline :2023-07-30
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Device Independent Quantum Key Distribution
The Inria research centre in Lyon is the 9th Inria research centre, formally created in January 2022. It brings together approximately 300 people in 16 research teams and research support services. Its staff are distributed at this stage on 2 campuses: in Villeurbanne La Doua (Centre / INSA Lyon / UCBL) on the one hand, and Lyon Gerland (ENS de Lyon) on the other. The Lyon centre is active in the fields of software, distributed and high-performance computing, embedded systems, quantum computing and privacy in the digital world, but also in digital health and computational biology.
Deadline : 2023-07-30
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Verified Offloading Orchestration of Network Functions at the Edge
The offered position is proposed by the RESIST team of the Inria Nancy Grand Est research lab, the French national public institute dedicated to research in digital Science and technology. The team is one of the European research group in network management and is particularly focused on empowering scalability and security of networked systems through a strong coupling between monitoring, analytics and network orchestration. This work is in the context of the HiSec project. The HiSec project is part of the 5G PEPR founded by the ANR, which focuses on cyber-security issues in future networks. These networks have played a key role in service delivery for digital infrastructures. These new networking technologies have also penetrated essential and critical services for our daily lives, such as energy, transportation or healthcare. The pervasive use of digital services and networks to control these critical infrastructures significantly increases the attack surface and the opportunities for attackers. We regularly observe attacks against these infrastructures, leading to successful compromise and very significant impacts. The objective of the HiSec project is thus to handle cybersecurity issues in these environments, and propose new mechanisms to protect these networks and detect attacks, attacks against the networking infrastructure itself, or against the services hosted or the users of the network.
Deadline : 2023-07-30
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(06) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD – Design and codesign of near term algorithms for quantum computing
We focus on developing advanced theoretical tools that can help understand the capabilities of quantum computers, improve their design for specific algorithms, and unlock new functionalities using quantum information processing. By taking this integrated approach, we hope to advance the state-of-the-art in Quantum Information Processing and
provide valuable insights for future developments.
Deadline :2023-07-31
(07) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Fast solvers for studying light absorption by nanostructured imagers
The exploitation of nanostructuring in order to improve the performance of CMOS imagers based on microlens grids is a very promising avenue. In this perspective, numerical modeling is a key component to accurately characterize and optimize the absorption properties of these complex imaging structures which are intrinsically multiscale (from the micrometer scale of the lenses to the nanometric characteristics of the nanostructured material layers). The present PhD project is proposed in the context of a collaboration between the Atlantis project-team of Inria research center at Université Côte d’Azur and STMicrolectronics (CMOS Imagers division of the Technology for Optical Sensors department) in Crolles. A Cifre funding will support this project. The objectives of the project are to design (1) a fast electromagnetic simulation approach based on a model reduction technique, to characterize numerically the light trapping in digital imagers exploiting nanostructured pixels and, (2) a multi-objective optimization strategy of the geometrical characteristics of the nanostructuring in order to simultaneously maximize the light absorption in a pixel and to minimize the crosstalk phenomenon between neighboring pixels. For the first time, in addition to the rigorous methods for solving Maxwell’s equations, we will be able to benefit from an alternative simulation approach based on model reduction. This new approach can be used in an optimization process and the expected gain in total computation time would be between 10 to 1000.
Deadline : 2023-07-31
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Fine-Grained Language Classification of Very Large Corpora
This position is part of Inria’s DEFI project COLaF (Corpus and Tools for the Languages of France), which is a collaboration between the Inria ALMAnaCH (Inria Paris center) and MULTISPEECH (Inria Nancy–Grand Est center) project teams. The objective of the project is to develop and make available digital linguistic technologies for the French-speaking world (native and non-native, contemporary or not, in France and outside of France, etc.) and the languages of France (all languages spoken in France: regional Romance and non-Romance languages, Creoles, immigrant languages, etc.), by contributing to the creation of inclusive data corpora, models, and software bricks. ALMAnaCH focuses on text and MULTISPEECH on multimodal speech. The two main objectives of this project are:
Deadline : 2023-07-31
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(09) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Self-supervised learning for implicit shape reconstruction
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 :2023-07-31
(10) 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 : 2023-07-31
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(11) 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 : 2023-07-31
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(12) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Physics-Based Motion Analysis for Interactive Free-Viewpoint Rendering of Captured Dynamic Scenes
The Inria centre at Université Côte d’Azur includes 37 research teams and 8 support services. The centre’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d’Azur, CNRS, INRAE, INSERM …), but also with the regiona economic players. With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d’Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.
Deadline : 2023-08-03
(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Investigating Hybrid Volumetric/Geometry Representations for Rendering and Interactive Editing of 3D Scenes
The Inria centre at Université Côte d’Azur includes 37 research teams and 8 support services. The centre’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d’Azur, CNRS, INRAE, INSERM …), but also with the regiona economic players. With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d’Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.
Deadline : 2023-08-03
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Machine learning for extreme weather forecasting
Extreme weather events, such as heat waves and extreme storms, can have outsized impacts on society, especially considering the resulting hazards, such as drought, wildfire, and flooding. Machine learning can help to improve the forecasting of such extreme events, which will be critical in helping communities adapt to a changing climate. The current practice of weather forecasting is primarily based on numerical weather prediction (NWP) which involves physics-driven simulations running on supercomputers. Running these NWP models is quite computationally expensive, and thus the forecasts are not updated in real-time. There’s currently a race among researchers in the tech industry to outperform NWP at weather forecasting, by training deep learning models on reanalysis data products (e.g. ERA5). After training (which requires significant GPU compute time), these data-driven models output forecasts much faster than standard NWP. While these data-driven models generally outperform NWP on average forecasts, they are not explicitly trained to forecast extreme events, and thus they tend to under-predict them.
Deadline : 2023-08-04
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD proposal – Modeling and Calibration of Crowd Behaviors in Public Spaces
At all these stages, crowd simulation is a useful technology for predicting crowd behaviour in existing venues or those under development, supporting the analysis of a situation as it unfolds, and providing scenarios for how a given situation might evolve. However, this technology is still not widely used in practice. One of the main reasons for this is the complexity involved in configuring a simulator to a specific situation, but also the actual ability to reflect crowd behaviour, which is highly dependent on the nature of the event and the facilities hosting it. The aim of this thesis is to extend the use of crowd simulators to the management of mass events by tackling these two stumbling blocks: the domain of validity and the automatic parameterisation of a simulation. The subject lies at the interface between image analysis techniques for gathering information on the situation and behaviour of a crowd, and the statistical modelling of their behaviour.
Deadline : 2023-08-04
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Next generation of development environments
Domain-Specific Languages (DSL) are now omnipresent in the industry and academy. Engineers and scientists are domain experts that handle DSLs to perform task specific to their job. In some way, DSLs are interfaces, at the good level of abstraction, that stand between domain experts and their engineering problems. Concretely, domain experts use DSLs through dedicated environments (IDE – Integrated Development Environment). In such environments, experts handle DSL models using standard interactive features (e.g. auto-completion, templating, error checking, navigation) and using the concrete syntax of the DSL, that can take various forms (e.g. graphical, textual, tabular). Experts use numerous DSLs broadly used in the industry, sometimes without knowing that they handle a DSL. For example, conceiving an air plane usually involves electricity, resistance, scientific computing schemas/models, that follow a specific nomenclature (i.e. the DSL grammar), with a specific representation (i.e. the DSL concrete syntax), with editing environments. Similarly, for conceiving a Web application experts may handle Docker, Git-Lab CI (continuous integration), ANTLR (grammar definition), CSS (style definition), Kubernetes (container orchestration) models/configuration files. All these languages are DSLs that experts use for completing a specific task. If a DSL works by itself, its use may impact other DSL models. For example, an electrician engineer that apply changes on his DSL models may have impacts on DSL models of other experts, such as on heating models. Each of those experts brings their own viewpoint, based on their expertise, for solving the global challenge, developping the system. This phenomenon is known as collective intelligence [1]. Current IDEs hardly support such collective intelligence as it requires novel features to share, communicate, explore, synchronize experts works. Moreover, Such features and the way they are used within a IDE depend on the experts domain. Langage engineers, that develop IDEs specifically for DSLs, thus struggle in coding by hand such complex features.
Deadline : 2023-08-15
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(17) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [PEPR SN AI4scMED] Single-cell multi-omics data integration for gene regulatory network inference
Within the framework of the PEPR project AI4scMED, in which Inria’s team BEAGLE collaborates with research groups in Grenoble, Montpellier, and Paris, you will develop methodological elements and algorithms for the integration of single-cell multi-omics data sets in the context of cell-based precision medicine. Your goal will be to facilitate the subsequent step of gene regulatory network inference, which is crucial for a mechanistic view on the regulatory processes ongoing in healthy and diseased cells. This is a three-year position for a PhD student. You will be advised by Anton Crombach and Thomas Guyet (HDR) (Inria Centre de Lyon), whilst working together with other members of Work Package 1.2 (N. Varoquaux, A. Cleynen, H. Isambert, L. Cantini) and members of the project AI4scMED. You will be located at Inria’s La Doua site in Villeurbanne / Lyon.
Deadline : 2023-08-16
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Efficicient task hybridization in heterogeneous computing : practical combinations of Control and Scheduling theories
The context of this work is the PULSE project where Inria and Qarnot Computing, with ADEME, are “PUshing Low-carbon Services towards the Edge”, with the aim of minimizing environmental impact in Edge Computing. In this domain, the Qarnot company distinguishes itself from traditional infrastructures by proposing a decentralized cloud solution that allows for reusing the heat dissipated by the servers in order to provide sites with high demands e.g. swimming pools, heat networks, industries etc. The CTRL-A research team is addressing these topics by developing a novel framework for model-based design of controllers in Autonomic Computing. We want to contribute generic Software Engineering methods and tools for developers to design appropriate controllers for their particular reconfigurable architectures, software or hardware, and integrate them at middleware level. We want to improve concrete usability of techniques from Control Theory by specialists of distributed systems.
Deadline :2023-08-20
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Energy efficient data management: Data reduction and protection meet performance and energy
The amount of data observed from the world is growing exponentially, reaching 64.2 zettabytes in 2020. To meet the continuously growing demand for computing resources to store and process Big Data, large cloud providers have equipped their infrastructures with millions of energy hungry servers distributed on multiple physically separate data-centers. This results in a tremendous increase in the energy consumed to operate these data-centers. However, as the data and the scale of data-centers are on the rise, energy consumption will continue to be a major concern in the Cloud. Thus, it is important to make data management in the cloud energy-efficient.
Deadline : 2023-08-20
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(20) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Dolev-Yao model-guided fuzzing of cryptographic protocols
The goal of this PhD thesis is to contribute to the DY Fuzzing project. This project proposes a novel and effective technique that we call Dolev Yao (DY) model-guided fuzzing, which precludes logical attacks against protocol implementations. The main idea is to consider as possible test cases the set of abstract DY executions of the DY attacker, and use a mutation-based fuzzer to explore this set. A first description of these ideas and a prototype implementatyion of a DY fuzzer are given in [1]. This first paper paves the way for a large number of follow-up works: plugging the fuzzer of different TLS implementations, designing a fuzzer for other protocols (e.g. DTLS, QUIC, WPA, …), designing better metrics to guide the fuzzer among others.
Deadline :2023-08-31
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Learning bimanual robot skills from human demonstrations and natural language
The team LARSEN is involved in the European project euROBIN. One of the main goals of the project is to advance cognition-enabled transferable embodied AI. Scientifically, it will substantially advance four core scientific topics: InterAct, Learning transfer, Transferable knowledge, and Human-center transfer. Three robotics domains are investigated: manufacturing, outdoor and personal robotics. In this project, Inria is leading the personal robotics challenge. In this project, INRIA is leading the personal Robotics Challenge, where bimanual manipulators and humanoid robots must execute a variety of complex manipulation, navigation and interaction tasks in a household scenario. Some of these tasks involve unloading a dishwasher, opening a fridge to take an object, folding clothes, carrying and handing objects to humans.
Deadline : 2023-08-31
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Decentralized learning of large-scale neural network models
This PhD position will take place in the Argo team of Inria Paris, located in the 12th arrondissement of Paris and close to gare de Lyon. The ARGO team works at the intersection of graph theory and machine learning, with projects ranging from distributed learning to learning and control with structured data. Moreover, this position is part of the Redeem projet of PEPR IA, a research initiative on Resilient, Decentralized and Privacy-Preserving Machine Learning involving 5 research teams located in Lille, Lyon, Paris and Saclay. The recruited person will have the opportunity to collaborate with other participants of this project and take advantage of the scientific emulation that the project will create.
Deadline : 2023-08-31
(23) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Thesis on Enhanced Deep Learning via Optimisation in Computational Imaging
The Inria Saclay-Île-de-France Research Centre was established in 2008. It has developed as part of the Saclay site in partnership with Paris-Saclay University and with the Institut Polytechnique de Paris .
Deadline :2023-08-31
(24) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Dynamic Parallelization of Sparse Codes for Machine Learning and High-Performance Computing
The Inria research centre in Lyon (previously the Lyon branch of the Inria centre in Grenoble) is the 9th Inria research centre, formally created in December 2021. It brings together approximately 270 people (including 110 Inria employees) in 15 research teams and research support services. Its staff are distributed at this stage on 2 campuses: in Villeurbanne La Doua (Centre / INSA Lyon / UCBL) on the one hand, and Lyon Gerland (ENS de Lyon) on the other. A third site should be opened in the course of 2022. The teams are mainly hosted with our partners. The centre’s teams work closely with research and higher education institutions (ENS de Lyon, UCBL, INSA Lyon, etc.), their laboratories, and other research organisations in Lyon (CNRS, INRAE, competitiveness clusters, etc.), but also with Lyon and regional economic players. Many international collaborations are also underway.
Deadline : 2023-08-31
(25) 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
(26) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Trustworthy AI hardware architectures
The direct consequence is the intense activity in designing custom and embedded Artificial Intelligence HardWare architectures (AI-HW) to support energy-intensive data movement, speed of computation, and large memory resources that AI requires to achieve its full potential. Moreover, explaining AI decisions, referred to as eXplainable AI (XAI), is highly desirable in order to increase the trust and transparency in AI, safely use AI in the context of critical applications, and further expand AI application areas. Nowadays, XAI has become an area of intense interest. AI-HW, similar to traditional computing hardware, is subject to faults that can have several sources: variability in fabrication process parameters, latent defects or even environmental stress. One of the overlooked aspects is the role that HW faults can have in AI decisions. Indeed, there is a common belief that AI applications have an intrinsic high-level or resilience w.r.t. errors and noise. However, recent studies in the scientific literature have shown that AI-HW is not always immune to HW errors. This can jeopardize all the effort of having an explainable AI, leading any attempt to explainability to be either inconclusive or misleading. In other words, AI algorithms retain their accuracy and explainability property under the condition that the hardware wherein they are executed is fault-free.
Deadline :2023-08-31
(27) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Primal and dual bounds for adjustable robust optimization
This thesis is proposed within the context of project DROI (Decision Rules for Optimization under Uncertainty) funded by ANR (Agence Nationale de la Recherche) under the grant number ANR-22-CE48-0018. The aim of this thesis is to advance the state-of-the-art of adjustable robust optimization. We will approach these problems both from the primal and the dual perspective, with the aim of providing exact solutions or approximate solutions with a measure of the optimality gap. From the primal side, we will study new classes of decision rules. This study will aim to improve current methodologies in terms of the quality of the solution obtained, and generality of applicability. From the dual side, we will study relaxations based on the Lagrangian relaxation of the coupling constraints or non-anticipativity constraints. This study will aim to improve current methodologies in terms of the dual bound provided.
Deadline : 2023-09-04
(28) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Hardware-guided compression & fine-tuning of Transformer-based models
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 : 2023-09-05
(29) 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 : 2023-09-16
(30) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Topology Design for Decentralized Federated Learning
The Inria centre at Université Côte d’Azur includes 37 research teams and 8 support services. The centre’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d’Azur, CNRS, INRAE, INSERM …), but also with the regiona economic players. With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d’Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.
Deadline : 2023-09-30
(31) 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 : 2023-09-30
(32) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Alternative approaches for privacy-preserving in federated learning
Inria is a national research institute dedicated to digital sciences that promotes scientific excellence and transfer. Inria employs 2,400 collaborators organised in research project teams, usually in collaboration with its academic partners.
This agility allows its scientists, from the best universities in the world, to meet the challenges of computer science and mathematics, either through multidisciplinarity or with industrial partners. A precursor to the creation of Deep Tech companies, Inria has also supported the creation of more than 150 start-ups from its research teams. Inria effectively faces the challenges of the digital transformation of science, society and the economy.
Deadline : 2023-09-30
(33) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Ensuring Availability of Internet-connected Constrained Wireless Networks
The PhD position in the scope of the PEPR 5G project HiSec. The HiSec project focuses on cyber-security issues in future networks. These networks have played a key role in service delivery for digital infrastructures. These new networking technologies have also penetrated essential and critical services for our daily lives, such as energy, transportation or healthcare.
Deadline : 2023-09-30
(34) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD student on federate learning and multi-party computation techniques for prostate cancer
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.
Privacy-preserving machine learning aims at learning (and publishing or applying) a model from data while the data is not revealed. Notions such as (local) differential privacy and its generalizations allow to bound the amount of information revealed. The goal of the multi-disciplinary FLUTE project is to advance and scale up data-driven healthcare by developing novel methods for privacy-preserving cross-border utilization of data hubs. Advanced research will be performed to push the performance envelope of secure multi-party computation in Federated Learning, including the associated AI models and secure execution environments.
Deadline : 2023-09-30
(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.
Privacy-preserving machine learning aims at learning (and publishing or applying) a model from data while the data is not revealed. Notions such as (local) differential privacy and its generalizations allow to bound the amount of information revealed. 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 : 2023-09-30
(36) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Verifying OCaml Programs With Exceptions and Control Effects
This job posting concerns a doctoral student position at Inria Paris. The student will be recruited by Inria Paris for a duration of 36 months. This position is funded by ANR project GOSPEL, a collaborative research
Deadline : 2023-11-30
(37) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Towards more solid basis for symmetric cryptography
During this PhD we will work on generalizing and improving the existing cryptanalysis families on symmetric cryptography.
Deadline : 2023-12-31
(38) 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 : 2023-12-31
(39) 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 : 2023-12-31
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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