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 Spatio-temporal modeling and AI tools for dose-response analysis and prediction of radiation-induced brain damage and cognitive impairment in patients treated with radiotherapy for glioblastoma.
This thesis aims at developing probabilistic ST models and AI tools to: a) estimate the potential associations between radiation-induced brain tissue modifications (as observed in MR brain images following RT), the dose of IR absorbed to the brain at a fine spatial scale (e.g. voxels of MR brain images) and the occurrence of cognitive impairment in patients treated with RT for glioblastoma ; b) predict the individual occurrence of cognitive impairment in these patients at an early stage after RT, with a quantification of the associated prediction uncertainties The work will be based mainly on data from the EpiBrainRad cohort [Durand et al. (2015)], which is one of the largest international prospective cohorts of patients treated with chemo-radiotherapy for glioblastoma and who have undergone standardised neuropsychological assessments. This cohort currently includes 224 adults treated for glioblastoma at the Hôpital de la Pitié-Salpêtrière (Paris) or at ICANS (Strasbourg). Since 2015, data are collected prospectively during the clinical follow-up of patients. For each patient, they include: a) clinical characteristics; b) multimodal MR brain images (collected before surgery, before RT and then every 2-3 months after RT), c) CT images used in the planning of brain RT treatment; d) results of an extensive battery of cognitive tests performed before RT and at 12, 24 and 36 months after RT.
Deadline : 2022-09-15
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Development of control strategies for synthetic microbial consortia (funded PhD offer)
The project is in the context of the ANR project Ctrl-AB (https://anr.fr/Projet-ANR-20-CE45-0014). It is focused on theoretical and applied control in a highly interdisciplinary context. Based in Grenoble within the Inria project-team MICROCOSME, it will be co-supervised by Eugenio Cinquemani (MICROCOSME, https://team.inria.fr/microcosme/eugenio-cinquemani/ – https://www.inria.fr/en/microcosme) and Jean-Luc Gouzé (BIOCORE, Inria Sophia-Antipolis, http://www-sop.inria.fr/members/Jean-Luc.Gouze/JLGouze-fra.html), both members of the ANR project CtrlAB. It will profit from the control-theoretic and systems-biology expertise of MICROCOSME and BIOCORE, as well as from the interaction with other experimental partners of CtrlAB.
Deadline : 2022-08-31
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Adaptive sampling strategies for nonlinear dimension reduction in uncertainty quantification.
Computational models from a wide range of fields, such as physics, biology, and finance, involve large numbers of uncertain input parameters. Quantifying the uncertainty caused by these random parameters is essential to improve the reliability of the models. Identifying which input parameters are the most relevant permits significant computational savings by putting the numerical effort onto the relevant parameters [1,2]. This dimension reduction step can be efficiently done using gradients of the model, if the latter are available [3,4].
Deadline : 2022-08-31
(04) 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
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(05) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H Détection d’anomalies pour l’inspection à grand rendement des ouvrages
L’objectif du travail est d’explorer ces voies de progrès. Dans un premier temps, il s’agira de réaliser un état de l’art méthodologique sur les différentes pistes citées. On pourra ensuite mettre en œuvre et évaluer des algorithmes d’apprentissage profond pour extraire les désordres : le/la doctorante aura à sa disposition des images d’ouvrages fournies par le Cerema.
Deadline : 2022-07-31
(06) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Time-guaranteed and reliable execution for safety-critical multicore systems
The safety-critical embedded industries, such as avionics, automobile, robotics and health-care, require guarantees for hard real-time and correct application execution. As applications become more complex, their computational demands scale rapidly, requiring architectures with multiple processing elements. Although multicore architectures can effectively satisfy the needs of best-effort systems, the same cannot be stated for critical embedded systems due to hard-to-predict timing behaviour and increased fault susceptibility [1].
Deadline : 2022-06-30
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(07) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Compositional verification of system program modules in Rust
Project RIOT-fp https://future-proof-iot.github.io/RIOT-fp is an Inria Challenge with the objective of developing future-proof operating system libraries for application to IoT: RIOT. Our PhD project is interested in one of the futures of RIOT: RIOT-rs, implemented in Rust. This computing base provides access to a vast ecosystem of analysis, code generation, verification and proof tools. 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 : 2022-06-30
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Ensuring confidentiality in modern Out-of-Order cores
This thesis will take place at Inria in Rennes, France, in the TARAN team and in collaboration with the LHS (high security laboratory). Inria Rennes has a vibrant community of 600 people, including researchers, engineers, …
Deadline : 2022-06-17
(09) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Temperature-Sensitive Intrusion Detection for Crystal-Free Networks
Apart from trusting its local clock that drifts, the nodes in the SCμM network must additionally use the time information provided by the network. The fact that timekeeping is no longer local opens up an attack vector: An attacker can disturb the network by heating up a subset of nodes to change their drift. In this thesis, we will research, design and implement an Intrusion Detection System (IDS) that applies machine learning techniques to network drift patterns in order to detect nodes under attack.
Deadline : 2022-06-11
(10) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Guess What I’m Learning: Side-Channel Analysis of Edge AI Training Accelerators
Summary: The importance of data privacy in Deep Learning (DL) systems is without doubt. However, recent studies have shown how to use side-channels to guess key parameters or recover inputs from DL model inference running on accelerators. For example, input images of a DL model were estimated from collected power traces without knowing the detailed model parameters [1]. However, this thesis goes further than current practice by studying if private information can be retrieved during training phase, if it is possible to disrupt the training quality, and how to secure training accelerators. The objective is to study training-time, side-channel analysis, hardware attacks and required countermeasures, focusing on fault injections in edge AI accelerators.
Deadline : 2022-06-07
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(11) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Privacy-Preserving Federated Machine Learning
The PhD student will be supervised by Aurélien Bellet, an Inria researcher in the Magnet project-team. Magnet (https://team.inria.fr/magnet/) is a research team that carries out research in Machine Learning in Information Networks, with an important focus on Natural Language Processing, Machine Learning under Privacy and Fairness Constraints, and Decentralized/Federated Learning. More specifically, the PhD will be part of the research project PRIDE (https://project.inria.fr/pride/) funded by the French National Research Agency (ANR).
Deadline : 2022-06-02
(12) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Integrated localization and mapping for autonomous vehicles
This position is part of a close partnership between the Valeo group and Inria (National Institute for Research in Computer Science and Automation), but also as part of a national collaborative research project of the relaunch plan of the automobile in which the RITS team of Inria and the DAR department of Valeo are partners.
The objective is to conduct research and contribute to the development of localization and mapping algorithms dedicated to autonomous vehicle with high integrity, for the transport of people or goods and operating in highway and urban environments. These modules will be validated on real instrumented prototypes belonging to the project partners.
Deadline : 2022-05-31
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(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Models and algorithms for statistical learning of spatio-temporal marked point processes. Application: cosmological data analysis and characterization.
The thesis will take place at the Institut Elie Cartan de Lorraine (IECL), the research mathematical institute of the University of Lorraine, within the Probability and Statistics team. The candidate will be also a member of the PASTA Inria team. The thesis advisor, Radu Stoica is a member of both these structures.
Deadline : 2022-05-31
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Digital reconstruction of plant seeds and multiscale morphomechanical modeling
The position is open in a highly interdisciplinary environment: the Mosaic team, composed by mathematicians, physicists and computer scientists, specialized in biophysics modeling and quantitative data analysis in the context of plant morphogenesis. The team belongs to the Plant Reproduction and Development lab, internationally-recognized for its expertise ranging from molecular genetics to biophysics modeling and systems biology. The lab is hosted on the ENS Lyon campus.
Deadline : 2022-05-31
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Visual perception and visual servoing for dexterous robotic manipulation of compliant objects
This PhD thesis takes place in the context of a research collaborative project called “BIFROST” whose main objective is to develop novel robot visual and tactile-based perception for manipulation of challenging compliant objects such as seafood. The project stems from a highly interdisciplinary consortium composed of three well-established entities: SINTEF (Norway), MIT CSAIL (USA) and Inria (France).
Deadline : 2022-05-31
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Modeling 6DoF Navigation and the Impact of Low Vision in Immersive VR Contexts
ANR CREATTIVE3D (https://project.inria.fr/creattive3d/) is a French National Research Agency funded project that aims to establish a framework for the creation of attention-driven 3D environments for training low-vision navigation tasks. For patients with age-related macular degeneration (DMLA in French), which results in the loss of central field vision obscuring part of their visual field, navigating complex and potentially dangerous environments with autonomy and safety is one of the most demanding and dangerous tasks. Immersive environments and virtual reality (VR) technologies hold a strong potential towards training for low-vision navigation tasks [Rap18]. Yet the use of VR in these contexts is impeded by the difficulty of creating adapted 3D content to simulate a large range of real-life situations, and to study its effectiveness for training and rehabilitation. This limits incentives for accompanying staff to familiarize with VR, and broadly adopt it. The project sets out from the study and then the modeling of user behavior during navigation tasks in context, and subsequently using this understanding for assisted creativity tools to design adapted training scenarios.
Deadline : 2022-05-31
(17) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H [DOCT2022-KAIROS] Génération de code source efficace pour le contrôle des systèmes synchrones critiques
Cette thèse a pour objectif de générer du code efficace (C ou C++ ou Rust) à partir d’une description CCSL (Clock Constraint Specification Language) et des règles opérationnelles de progression du système. CCSL permet de décrire non pas une application entièrement, mais uniquement le comportement de ses horloges. Une horloge permet de déclencher ou pas l’exécution d’une fonction ou d’une tache à un instant précis. CCSL n’est pas un langage de programmation qui permet d’exprimer l’algorithmique des fonctions, il exprime uniquement l’instant de leur exécution. Le code généré doit pouvoir efficacement permettre de calculer les valeurs de ces horloges logiques et de les combiner au code du système. Il y aura deux problèmes principaux à aborder :
Deadline : 2022-05-25
(18) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H [DOCT2022-COFFEE] Schémas volumes finis sur grilles décalées pour les écoulements multifluides
L’objet de cette thèse est d’élaborer une stratégie numérique de type « volumes finis sur grilles décalées » pour traiter des écoulements multifluides multidimensionnels avec des maillages généraux. L’objectif est notamment de viser la simulation de la formation de profils de sédimentation pour des écoulements fluide-particules.
Deadline : 2022-05-25
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-DIANA] Leveraging the wealth of available data for network monitoring and troubleshooting
Despite the considerable improvement we saw recent years in terms of internet access performance and the quality of the physical and virtualised infrastructures hosting the internet services, we are still facing a lot of situations where the internet service degrades and the end user Quality of Experience (QoE) is less than expected. The reasons are many, from the slowness of the device of the user, to the bad configuration of the WiFi at home, to the interference caused by the neighbouring WiFi networks, to the impairments caused by the cellular network infrastructure and the mobility of the user, to the saturation of the access link by the many devices and applications running at home, to the congestion in the ISP network especially on its peering links, till the overload of the servers of the content providers following a sudden increase in the users’ activities. There are also situations where the QoE degrades for other reasons than congestion or lack of resources, as when the ISP or the content providers decide to reduce the quality of their service to prioritise some part of the traffic over the rest a.k.a. network traffic differentiation, or to face scenarios of heavy service usage (video resolution reduction by major video stream platforms in confinement period). Those situations, and many others, exist well today and will not be solved in the immediate future despite the considerable advances seen and foreseen both at the network and the cloud levels. The problem is not only in the frustration they cause for the end user, but also in the difficulty for the end user to distinguish between them so as to be able to take the appropriate actions to counter their origins in the limit of possible.
Deadline : 2022-05-25
(20) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-BIOCORE] Ecophysiological modeling of plant-nematode interactions. Understanding the origins and consequences of differential plant susceptibility
The PhD student will join the BIOCORE team (Inria, INRAE, CNRS-Sorbonne Université) and the M2P2 Models and Methods for Plant Protection team at ISA Institut Sophia Agrobiotech (INRAE, CNRS, Université Côte d’Azur).
The PhD student will interact with ISA biologists from the IPN Plant-Nematode Interactions team and partners from the seed company Vilmorin & Cie.
Deadline : 2022-05-25
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-ACUMES] Multi-physics couplings using isogeometric analysis
The doctoral student will be part of Acumes Project-Team at Inria Sophia-Antipolis Research Center. At first, he/she will have to formalize the model coupling in the context of the isogeometric method. Fluid- structure interactions are espacially targeted, by using a continuous Galerkin formulation for the structural model and a discontinuous one for the fluid model. The coupling between the two models will be achieved by an exchange of data (efforts, displacements) through the common parameterized interface. He/she will in particular investigate different exchange strategies and time integration approaches.
Deadline : 2022-05-25
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-CAMIN] Estimation and prediction of human motion by numerical trajectory optimization for musculoskeletal models.
This thesis has three main objectives:
1.) To develop numerical models of muscle that are physiological while being compatible with optimization algorithms (continuity, differentiability) [4]. Particular attention will be paid to the dynamic behavior of these models (stability, steady state behavior), in order to make possible the analytical resolution of some differential equations involved in the different dynamics.
2.) To integrate these models into the rigid body dynamics calculation library, Pinocchio. Pinocchio is a state-of-the-art software for calculating the motion of polyarticulated rigid body systems (such as robots, skeletal models of the human body, etc.). Coded in C++, it is based on Eigen for linear algebra and on FCL for collision detection. In order for Pinocchio to extend beyond its initial field of application (robotics), an additional functionality is needed: muscle actuation. With this addition, it will become possible to animate musculoskeletal models from motor neuron excitation to body movement. This improvement requires :
- extending the model definition from purely skeletal models to musculoskeletal models
- designing associated visualization objects inside the Meshcat viewer
- adding the notion of actuators that provide torque to joints
- implementing the muscle models developed in 1.)
3.) To test the implementation and the developed models on practical cases of optimal control. Several options can be tested and compared: multiple shooting [5], differential dynamic programming [6] and direct collocation [7]. There is not yet a consensus in the literature on the superiority of one of these approaches over the others. A practical application envisaged in the framework of the CAMIN team’s clinical experiments is the real-time estimation of muscle forces induced by functional electrical stimulation to quantify the movements produced.
Deadline : 2022-05-25
(23) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Stateful and distributed data stream processing
The data produced by the Internet of Things are often generated at the edge of the Internet in the form of data streams. Instead of always transferring them to the cloud to be processed there, a more efficient alternative exploits edge/fog computing technologies to process the data close to the location where they were created. This reduces the usage of long-distance networks and improves the response times. Data stream processing frameworks such as Apache Flink are well-suited for processing these data streams in real time. However, using these frameworks in geo-distributed environments such as edge/fog platforms incurs significant challenges.
Deadline : 2022-05-25
(24) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-MCTAO] Observability and observer synthesis for Wilson-Cowan equations
The primary visual cortex V1 is an area of the brain responsible for a first treatment of images arriving from the retina. High level geometric models of V1 proved to be remarkable in their predictive capability. Wilson-Cowan equations, based on averaging the discrete structure of the cortex, have been successfully used, in particular, to identify recurring visual hallucinatory patterns. These nonlinear integro-differential equations, where an integral kernel encodes mutual activity inhibition and excitation between neurons based on their relative positions, are used to model neuronal activity in cortical areas.
Deadline : 2022-05-25
(25) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-INDES] Optimistic Gradual Typing for TypeScript
Nowadays, JavaScript is no longer confined to the programming of web pages. It is also used for programming server-side parts of web applications, compilers, and there is a growing trend for using it for programming internet-of-things (IoT) applications. All major industrial actors of the field are looking for, or are already providing, JavaScript based development kits (IoT.js, Espruino, JerryScript, Kinoma.js, …). In this application domain, JavaScript programs execute on small devices that have limited hardware capacities, for instance only a few kilobytes of memory. Just-in-time (JIT) compilation, which has proved to be so effective for improving JavaScript performances, is unthinkable in these constrained environments. There would be just not enough memory nor CPU capacity to execute them at runtime.
Deadline : 2022-05-25
(26) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-BIOCORE] Optimal resource allocation in mathematical models of micro-organisms under dynamic environmental conditions
The Inria Sophia Antipolis – Méditerranée center counts 34 research teams as well as 8 support departments. The center’s staff (about 500 people including 320 Inria employees) is made up of scientists of different nationalities (250 foreigners of 50 nationalities), engineers, technicians and administrative staff. 1/3 of the staff are civil servants, the others are contractual agents. The majority of the center’s research teams are located in Sophia Antipolis and Nice in the Alpes-Maritimes. Four teams are based in Montpellier and two teams are hosted in Bologna in Italy and Athens. The Center is a founding member of Université Côte d’Azur and partner of the I-site MUSE supported by the University of Montpellier.
Deadline : 2022-05-25
(27) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-COATI] Algorithmic aspects and random network models for temporal brain networks
A mathematical object that has come to play a fundamental role in today’s science is that of Graph or Network [EK10]. As the theory developed and applications unfolded, in the last couple of decades scientists started considering a temporal generalization of the concept of networks, where edges can appear and disappear [CD15]. Such a new area of research, which most commonly goes under the name of temporal networks, is nowadays developing quickly, both in theoretical computer science and other mathematical fields, and in other applied sciences [C18]. Many applied sciences are trying to abstract their data as a temporal network with the hope that such coarse representation may unveil subjacent structures, while theoretical scientists are concerned with the design of efficient algorithms to analyze their mathematical properties [MS18]. One rapidly emerging domain in that respect is the study of the temporal activation of brain areas observed through functional magnetic resonance imaging, which is offering a new perspective on a growing number of psychiatric and neurological conditions [LD17, KW15, JJ17, SP10, DS18, JVM12].
Deadline : 2022-05-25
(28) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-ACENTAURI] Efficient polynomial systems solvers for large scale robotic problems
In this PhD we will focus on the optimization of polynomial cost functions since the number of equilibrium points (global minimum, local minima, saddle points) can be deterministically numbered. Indeed, when the cost function is a polynomial function the optimal solution can be obtained by solving a polynomial system of equations [5]. For such problems, we can find a ”closed form” using only standard linear algebra operations: matrix decomposition (LU, QR, SVD, …), eigenvalues and eigenvector computations, etc. Many of the state-of-the-art specific polynomial systems solvers are based on Gr¨obner bases and the action-matrix method [5]. There are now powerful tools available for the automatic generation of efficient Gr¨obner basis solvers for [8, 9, 11]. Such methods work extremely well for problems of reasonably low degree, involving a few variables. Currently, the limiting factor in using these methods for larger and more demanding problems are numerical difficulties. When considering larger problems numerical stability is still an issue [3]. Another approach to polynomial system solution based on generalization of the homogeneous resultant introduced by Macaulay [12] to multivariate homogeneous polynomials. Resultant based approaches [2, 15] can be divided into u-resultant where an additional equation is added to the system of h-resultant where one of the unknown is hided in the coefficients. In both cases the solution is found by computing the eigenvalues (u-resultant) or the generalized eigenvalues (h-resultant) of matrices which size (and computation time) depends on the number of unknowns and the degree of the polynomials. For sparse polynomial systems it is possible to obtain more compact resultants using Sparse Resultants [7, 16]. Further improvements in efficiency can be obtained considering symmetries in the polynomials [10].
Deadline : 2022-05-25
(29) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H [DOCT2022-ABS] Effective algorithms for the statistical physics of biomolecules
Institutional Context. The Algorithms-Biology-Structure project carries out research at the interface between theoretical computer science (geometric and topological modeling, optimization, graph theory, machine learning), and computational structural biology / biophysics. The overarching goal is to unveil the relationship between the structure and dynamics of biomolecules and their functions, with applications in biology and medicine, see http://team.inria.fr/abs
Deadline : 2022-05-25
(30) PhD Degree – Fully Funded
PhD position summary/title: Doctorant F/H [DOCT2022-ABS] Designing movesets for whole proteins
PhD topic-specific goals. The design of movesets for proteins usually distinguishes the protein backbone–for which methods from inverse kinematics are used [1], and the side–for which libraries of side chain conformations are at play. In recent work, we have proposed a novel paradigm to sample protein backbones [2,3,4]. The method combines novel mathematical insights into the so-called Tripeptide Loop Closure [2], with a Markov Chain Monte Carlo sampling method called Hit-and-Run [5,6]. The goal of the thesis will be to extend this method to also incorporate multi-scale models of side chain conformations. The movesets obtained should be suitable for structural but also thermodynamic analysis. The methods used will borrow from computational geometry, numerical mathematics, kinematics, and machine learning. Implementation and tests will be conducted in the scope of the Structural Bioinformatics Library, see http://sbl.inria.fr
Deadline : 2022-05-25
(31) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-STARS] 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 : 2022-05-25
(32) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-COMPO-EPIONE] Optimizing sequential treatment in head and neck squamous cell carcinoma (HNSCC): artificial intelligence based on real-life patient data to support medical decision-making
This PhD proposal will take place within a collaboration between the Inria – Inserm team COMPO (co-supervision by Dr S. Benzekry), EPIONE (co-supervision by Dr I. Balelli) and AP-HM (co-supervision by Pr A. Varoquaux, radiologist). The recruited student will share time between the three locations. COMPO (COMputational Pharmacology in Oncology, Marseille), is composed of mathematicians, pharmacists and clinicians and is a unique multidisciplinary environment focused on developing novel computational tools for decision- making in clinical oncology. Second location is the Inria team EPIONE, specialized in computational image analysis. The third location will be in the radiology service of A. Varoquaux (AP-HM).
Deadline : 2022-05-25
(33) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M [DOCT2022-STARS] Doctorant F/H Computer Vision / Deep Learning: Video Generation
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 : 2022-05-25
(34) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Multimodal automatic hate speech detection
Hate speech expresses an antisocial behavior. The topics of hate can be gender, race, religion, ethnicity, etc. (Delgado et al., 2014). There is no clear definition of the term hate speech. The Council of European Union defines hate speech as: “All forms of expression which spread, incite, promote or justify racial hatred, xenophobia, antisemitism or other forms of hatred based on intolerance, including intolerance expressed by aggressive nationalism and ethnocentrism, discrimination and hostility towards minorities, migrants and people of immigrant origin”.
Deadline : 2022-05-23
(35) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Acoustic to Articulatory Inversion by using dynamic MRI images
This project is a LUE (Lorraine Université d’Excellence) project; it will be conducted jointly by the Loria laboratory (MultiSpeech team) and the IADI laboratory (INSERM U1254), which have been working together for several years on speech production and vocal tract imaging.
In particular, this will allow us to use the two-dimensional MRI acquisition system in real time (at 50 images per second) of the IADI laboratory. This system, unique in France, enables imaging the vocal tract at a frequency of 50 Hz in any direction, which is interesting for the recovery of the area function.
Deadline : 2022-05-18
(36) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Learning-based Decentralized Control of Groups of Multiple Robots
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 : 2022-05-16
(37) 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 : 2022-05-15
(38) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD Position F/H Virtual Collaborative Jeu de Paume
As part of a collaboration between the 2 teams Inria MimeTic and Hybrid, this project funded by EUR Digisport is part of an interdisciplinary context that combines Virtual Reality, Sport, and Heritage.
With the development of immersive technologies for the masses, using VR for sports training has become a valuable solution to train specific subskills with more engagement, motivation, and with new training paradigms. VR offers new possibilities as the system can trick with physics laws, and provides a unique control on multisensorial feedback. In this project we explore another facility that consists in enabling distant people to compete or train themselves in competition conditions.
Deadline : 2022-05-07
(39) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M ThurstonVR – Réalité virtuelle dans des espaces non-euclidiens
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 : 2022-05-07
(40) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M (BMI2022) Aggregation techniques for solving large-scale network flow formulations
Our research interests lie in the field of operations research (O.R.) and integer programming. Our goal is to propose mathematical methods and algorithms for abstract models that can be specialized to address a large number of problems. Our main methodological tools are based on decomposition methods and so-called extended integer programming formulations. Our expected contributions go from theoretical studies of problems and abstract models to algorithms and their efficient implementation in decision-support tools. To maximize our impact, we will develop high-level open- source interfaces for our methods, which will allow them to be used by a larger community of O.R. practitioners and decision makers.
Deadline : 2022-05-05
(41) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M (BMI2022) Modeling of sustainable ICT and AI sectors with respect to environmental limits
The manao project aims at studying how light, matter and shape act together in synergies, at the convergence of Digital Optics and Computer Graphics, providing for more powerful representations of appearance. Such a high-level approach is to contrast with the main trend of modern Computer Graphics to study light, shape and matter separately.
Deadline : 2022-05-05
(42) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M (BMI2022) Combinatorial optimisation problems for reverse ecology
The study of biology combines studies of forms (diversity) and modelling of processes (functional or evolutionary). Pleiade addresses the dual challenge of rapidly measuring relevant dissimilarities between biological objects and exploring the relationships between trait diversity and functional diversity at multiple scales. We develop algorithms, models, and software frameworks for applications in ecology, evolution and biotechnology.
Deadline : 2022-05-05
(43) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M (BN2022) Information visualization for effective altruism
Background: Effective altruism is a movement whose goal it to use “evidence and reason to figure out how to benefit others as much as possible” [1]. It focuses in particular on alleviating global suffering through charitable donations, but distinguishes itself from most charitable endeavors through its focus on maximizing the amount of good a given donation can make. This movement can greatly benefit humanity, but there is little awareness about it including among regular donors, and even people who adhere to it lack tools to help them understand humanitarian trade-offs and make good decisions. Information visualization could help alleviate these two issues. Information visualization is the study of computer-supported, visual representations of data meant to support understanding, communication, and decision making. The goal of this thesis will be to study how to use information visualization to promote effective altruism, i.e., finding ways of using visual and possibly interactive representations of data to i) explain effective altruism and/or ii) help people make more effective humanitarian decisions. This is a vast topic on which there has been virtually no research so far, and part of the student’s work will be to find out which directions of research are worth pursuing, and which of those they would personally like to pursue. A direction that seems particularly interesting and novel is the use of non-conventional ways of visualizing information for the purposes of effective altruism, such as visualizations that go beyond standard computing devices and tap into emerging technologies like virtual reality, augmented reality, ambient displays, and physical representations. For more on this, see [2].
Deadline : 2022-05-05
(44) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Pattern-avoiding inversion sequences: enumeration and limit shapes
First, the PhD candidate should contribute to the research effort in enumerative combinatorics of pattern-avoiding inversion sequences. The expected results are new enumeration results for some families of pattern-avoiding inversion sequences. One suggested method to achieve this goal is the approach through generating trees. We are already aware of two possible growths for inversion sequences which can lead to interesting generating trees when some patterns are avoided. In addition, we aim at developing extensions of the method of generating trees, with applications to pattern-avoiding permutations, but possibly also to pattern-avoiding inversion sequences.
Deadline : 2022-05-04
(45) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD Position / Quantum programming with (co)inductive types.
This PhD project aims at studying substructural and quantum type systems with inductive and coinductive types. The applicant will design and study the type-theoretic, operational and denotational aspects of the corresponding languages and systems.
Deadline : 2022-05-02
(46) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Meshing Singular Surfaces – Application in Robotics
The goal of this project is to provide fast and reliable surface plot tools for researchers in mechanical design and control theory, with a focus on the triangulation of singular surfaces that are the solutions of algebraic or analytic equations and inequalities.
A classical way to represent a singular surface is to decompose it in smooth cells of dimension 0, 1 and 2. A topologically correct meshing of a singular surface must respect these features. The 2-dimensional cells are subdivided by triangles and the singularities (0 and 1-dimensional cells) are identified as special vertices and edges.
Deadline : 2022-05-02
(47) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Nongaussian models for deep learning based audio signal processing
The PhD student will join the Multispeech team of Inria, that is the largest French research group in the field of speech processing. He/she will benefit from the research environment and the expertise in audio signal processing and machine learning of the team, which includes many researchers, PhD students, post-docs, and software engineers working in this field.
Deadline : 2022-05-02
(48) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Computational Design of Auxetic Metamaterials
In this Ph.D. thesis, we focus on a class of metamaterials, called auxetics [1]. Auxetic materials have a counter-intuitive deformation behavior: instead of becoming thinner when stretched, they become thicker. Auxetic materials are known to exhibit properties important in applications as diverse as biomedical engineering, aerospace industry, or protective sports gear, among others.
Deadline : 2022-05-02
(49) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Explainability and Interpretability in Probabilistic Planning
The objective of this PhD thesis is to propose a systematic method to describe, formalize and solve any problem combining a planning task and a willingness to control or optimize some informations held by one actor or the other, human or agent.
Deadline : 2022-05-02
(50) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Paraphrase Modeling with Abstract Categorial Grammars
The Sémagramme team develops theoretical and practical tools for natural language modeling and processing. It puts a strong focus on descriptions and models of linguistic structures, such as tree or graph parse structures, or semantic representations. To this end, Sémagramme has developed the Abstract Categorial Grammar formalism (ACG, de Groote 2001). It is a grammatical framework in which the encoding of different grammatical formalisms is possible, for instance context-free grammars, tree adjoining grammars (TAG, Joshi and Schabes 1997), etc. It relies on languages of λ-terms, that generalize string and tree languages.
Deadline : 2022-05-02
(51) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M In situ semantic reconstruction for spontaneous augmented reality
The objective of this thesis is to allow a user to incrementally reconstruct, in three dimensions, an architectural environment by physically moving in the scene. The generated model will consist of surface or volume primitives (rectangles, boxes, ellipsoids, etc.), associated with semantic classes (ground, façade, building, tree, etc.). This type of representation is particularly adapted to CAD (Computer Aided Design), 3D computer graphics and GIS, where the objects manipulated must be both compact and informative. It is also very interesting for augmented reality (AR) since it facilitates the registration of the 3D model in video images [1,2] and the placement of virtual objects in relation to objects in the real scene.
Deadline : 2022-05-02
(52) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Hybrid CNN-Snake algorithms for the quantitative analysis of 3D live cell images
The goal of the thesis is to develop generic image analysis algorithms for the characterization of spatiotemporal events observed in 3D time-lapse microscopy imaging. In particular, we will investigate innovative approaches to segment and track mobile cellular entities or aggregates that can divide or fuse over time. From a methodological point of a view, we will focus on hybrid methods that bring together deep learning approaches and active contours (a.k.a. snakes). The proposed research is then at the frontier of applied mathematics, image processing/analysis, and computer science.
Deadline : 2022-04-30
(53) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Flexible resource allocation for FaaS applications in the fog
The PhD student will work in the MYRIADS team, part of IRISA and Inria Rennes – Bretagne Atlantique. 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 a lively city and a major center for higher education and research. Rennes is easy to reach thanks to a high-speed train line to Paris.
Deadline : 2022-04-30
(54) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Optimization of acquisition in diffusion MRI towards quantitative connectivity
The PhD will be prepared in the Empenn research team, under the joint supervision of Isabelle Corouge and Emmanuel Caruyer. The objectives of the PhD are at the heart of the MMINCARAV Associate team between Empenn and the LTS5, EPFL (Lausanne, Switzerland), funded since 2019 by Inria (application for the renewal of this collaboration will be sent for 2023-2025). In the context of this collaboration, scientific exchange and visits to EPFL will be organized yearly. The experimental part of the project will benefit from the Neurinfo imaging facility, equiped with a Siemens CONNECTOM Prisma 3T scanner; a dedicated diffusion MRI sequence for arbitrary diffusion-encoding gradients was developed in the context of a Master research agreement with Siemens Healthineers.
Deadline : 2022-04-30
(55) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Data-driven anticipation for whole-body teleoperation of humanoids
The objective of this PhD is to design a whole-body teleoperation system that anticipates the motion of the operator. It will be demonstrated on the TALOS humanoid robot of Inria Nancy – Grand Est / LORIA, a full-sized, state-of-the-art humanoid robot. The PhD will combine two highly dynamic scientific fields:
- machine learning to learn trajectories of the humans and build predictors of future motions given current motion;
- whole-body model predictive control [3] to use the predictions to improve the accuracy and the balance of the robot, especially when performing fast movements
Deadline : 2022-04-30
(56) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Accurate and robust automated detection and segmentation of Multiple Sclerosis lesions in spinal cord MRI
Selected PhD candidate will join the research lab Empenn in Inria-Irisa, located in Rennes, France. Empenn (https://team.inria.fr/empenn) is jointly affiliated with Inria, Inserm (National Institute of Health and Scientific Research), CNRS (INS2I institute), and the University of Rennes I. The Empenn group operates the Neurinfo imaging facility in the context of a partnership with the University Hospital of Rennes, Inria, the CNRS, and the Cancer Research Center. The team has access to several computing facilities and established collaborations with other Inria/Irisa research teams in the field of machine learning.
Deadline : 2022-04-30
(57) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Mechanistic modeling of circulating DNA combined to machine learning for prediction of response and survival following immunotherapy
The position will be located in the Inria-Inserm team COMPO (COMputational Pharmacology in Oncology), located in the University Hospital of Marseille (AP-HM). The team is composed of mathematicians, pharmacists and clinicians and is a unique multidisciplinary environment focused on developing novel computational tools for decision- making in clinical oncology.
The project will consist in working within the SChISM (Size Cfdna Immunotherapies Signature Monitoring) clinical study, in collaboration with AP-HM and the id-Solution and ADELIS biotechs. The PhD student will be co-supervised by a mathematician (Dr S. Benzekry) and a clinical oncologist (Pr S. Salas).
Deadline : 2022-04-29
(58) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Secure Deep Learning Hardware Accelerators Against Fault Injection and Side-Channel Attacks
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 : 2022-04-23
(59) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD thesis on Natural Language Processing approaches in the musical domain : suitability, performance and limits
The main goal of this research will be to evaluate the adaptability, performance and relevance of NLP techniques when applied to the symbolic musical domain.
The Inria Lille – Nord Europe research centre, created in 2008, has a staff of 360, including 305 scientists in 15 research teams. Recognised for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria Lille – Nord Europe research centre pursues a close relationship with large companies and SMEs. By promoting synergies between researchers and industrialists, Inria participates in the transfer of skills and expertise in digital technologies and provides access to the best European and international research for the benefit of innovation and companies, particularly in the region.
Deadline : 2022-04-22
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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