[🟢 OPEN CALL] COFUND DeMythif.AI - Call for application 2024
[🟢 OPEN CALL] COFUND DeMythif.AI - Call for application 2024
- More information
- Timetable for 2024-2025
- Details of how to apply on ADUM?
Paris-Saclay University COFUND DeMythif.AI call
for international applications for the doctoral program
Paris-Saclay University has launched a call for applications for 21 fellowships on 48 possible PhD topics on the general theme of “ AI and uncertainty ”. This call will close on January 17th 2025, at 23:59 CET.
The 21 successful candidates will receive full funding for a 3-year PhD, starting in autumn 2025. For each selected candidate, the Marie Sklodowska Curie DeMythif.AI European Action funds a doctoral scholarship of excellence, with a salary in line with the French Ministry of Research scholarship, funding for entry mobility and mobility during the PhD. DeMythif.AI students will benefit from dedicated events, specific doctoral training and the opportunity to spend up to three months in an external company or laboratory, thanks to the support of complementary activities.
The DeMythif.AI “AI and Uncertainty” theme is broad: controlling uncertainties, managing explicability and encouraging frugality, across a wide spectrum of applications in fundamental or applied sciences and engineering. These PhD topics are hosted in top-level laboratories at the Université Paris-Saclay and supervised by leading researchers to train the next generation of AI scientists to answer exciting questions in diverse scientific fields. Some PhDs are co-funded by companies.
DeMythif.AI is supported by CNRS, CEA, INRIA, INRAE and Onera, as well as IFPEN, LNE and ILLS, GIS LARTISSTE, IRT SystemX, EDF, GE Healthcare, IBM, RTE, Safran, Sanofi, SLB, startups Quantmetry, Cairnbio, LightOn and Phimeca.
👉For all questions relating to international hosting (visas, accommodation, etc.), please consult the Paris-Saclay University International Hosting Center page.
👉 Questions about the DeMythif.AI program in general and the selection process should be sent to demythifai-contact@inria.fr.
Subjects are sorted by doctoral school and then by host laboratory. In some cases, an additional pdf with scientific details may be provided.
Laboratory : Formal Methods Laboratory (LMF) - Université Paris-Saclay, CentraleSupélec, CNRS
- AUTOPSY : Automating Cognitive Behavioral Therapy Modules
- FORMAPSY : Formalizing Psychological Theories
Laboratory : Centre Inria de Saclay - Île-de-France
Laboratory : Données Algorithmes pour une Ville Intelligente et Durable (DAVID) - UVSQ
- Generative AI, meta-learning, and object detection for identification and analysis of driving situations in urban environments: toward enhanced safety for autonomous vehicles
- Hypergraph Deep Neural Networks based on Game Theory
Laboratory : Laboratoire Interdisciplinaire des Sciences du Numérique (LISN) - Université Paris-Saclay
Laboratory : Laboratoire des Signaux et Systèmes (L2S) - CentraleSupélec, CNRS, Université Paris-Saclay
- Reduced-complexity reservoir computing via time-delay approaches
- Accelerated Diffusion Processes for Uncertainty Quantification in Image Reconstruction based on a Low Rank Model
- Climate Projections Using Explainable Machine Learning Approaches
Laboratory : Traitement de l'Information et Systèmes (TIS) - ONERA
- Bio-inspired neural models for artificial intelligence and computer vision
- LOX-Methane Atomization Model from Morphological Description
Laboratory : Laboratoire des systèmes et Applications des Technologies de l'Information et de l'Energie (SATIE) - ENS Paris-Saclay
Laboratory : Informatique, BioInformatique, Systèmes Complexes (IBISC) - UEVE
Laboratory : Centre de Vision Numérique (CVN) - CentraleSupélec, Inria, CNRS
Laboratory : Institut de Chimie Physique (ICP) - Université Paris-Saclay, CNRS
Laboratory : Nanosciences et Innovation pour les Matériaux, la Biomédecine et l’Énergie (NIMBE) - CEA, CNRS, Université Paris-Saclay
Laboratory : Energétique Moléculaire et Macroscopique, Combustion (EM2C) - CentraleSupélec, CNRS
- Machine learning assisted design of porous media for process engineering
- Physics-informed reduced-order modeling for digital twins of sustainable combustion systems
Laboratory : Laboratoire de Mécanique Paris-Saclay (LMPS) - ENS Paris-Saclay
- Super-resolved generative and space-time adaptive neural operator for 3D extreme-scale wave propagation problems
- Robust multiphysics topological optimization: application to electrical machines
- A data driven mechanical characterization of bone aging based on infrared spectroscopy
- Toward interpretable real-time quantification of uncertainties in the control of cardiac disease in any given specific patient with thermodynamically consistent Kolmogorov-Arnold networks using the concept of modified Constitutive Relation Error (mCRE) within the framework of isogeometric analysis
Laboratory : Laboratoire de Mécanique et d'Energétique d'Evry (LMEE) - UEVE
Laboratory : Industrial Engineering (LGI) - CentraleSupélec
Laboratory : Centre Borelli - ENS Paris-Saclay
Laboratory : Mathématiques et Informatique Appliquées du Génome à l'Environnement (MaIAGE) - INRAE
Laboratory : Département de Physique des Particules (DPhP) - CEA Irfu
- Machine learning for visual inspection and final state reconstruction in the ATLAS experiment
- Development of an AI-based framework in Neutrino Physics: a focus on time series event reconstruction and multivariate science analyses
- Artificial Intelligence to simulate Big Data and Search for the Higgs Boson Decay to a pair of Muons with the ATLAS Experiment at the large Hadron Collider
Laboratory : Département d'Électronique des Détecteurs et d'Informatique pour la Physique (DEDIP) - CEA
Laboratory : Laboratoire de Physique des deux Infinis Irène Joliot-Curie (IJCLab) - CNRS, Université Paris-Saclay, Université Paris-Cité
- Machine learning algorithms for the analysis of time-of-flight mass spectra with a gold nanoparticle probe: Classification, quantification and identification of complex compounds
- Transfer Learning Approaches Leveraging Nuclear Ab Initio Reaction Models
- Challenging neutrino events reconstruction in the DUNE liquid argon time projection chamber with advanced machine learning methods
Laboratory : Laboratoire de Physique des Solides (LPS) - CNRS, Université Paris-Saclay
Laboratory : Institut d'Astrophysique Spatiale (IAS) - CNRS, Université Paris-Saclay
Laboratory : Astrophysique Instrumentation Modélisation (AIM) - CEA Irfu, Université Paris-Cité
Laboratory : Institut des Sciences du Vivant (BAOBAB) - CEA
Laboratory : Laboratoire d’Imagerie Biomédicale Multimodale Paris-Saclay (BIOMAPS) - Université Paris-Saclay
Laboratory : Charles Fabry (LCF) - IOGS, CNRS, Université Paris-Saclay
Laboratory : Group of Electrical Engineering - Paris-Saclay (GeePS) - CentraleSupélec
- Development of a digital twin of electric actuator: approach based on physical informed machine learning model
- Intelligent Electrical Engineering: Developing Next-Gen Simulation Tools with PINNs and Machine Learning
- Physics-inspired artificial intelligence for diagnosing insulation failures in an automotive traction chain
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The call closes on January 17th, 2025 23:59 CET;
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Students of all nationalities must meet the MSCA criterion of not having spent more than 12 months in France since January 18th, 2022;
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Students must hold a master's degree in computer science or applied science related to the thesis subject; the exact rule depends on the doctoral school in which the thesis subject is registered;
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Students must have a level of C1 or equivalent in English. No French is required;
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Students must not apply for more than 3 subjects;
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An initial shortlist of 45 candidates will be made on the basis of academic qualifications and documents submitted, including three letters of recommendation;
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If they apply for more than one subject, they will be asked to rank them in order of preference;
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The 45 shortlisted candidates will be interviewed remotely to present their topic and answer the jury's questions;
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The selection committee, made up of renowned international specialists, will select the 15 best candidates, plus a complementary list, before May 2024.
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October 25, 2024 l Deadline for submission of thesis topics on ADUM (presentation of scientific background, topic, host team, possible co-funding)
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❗November 2024 - January 17, 2025 l Publication of subject, submission of student applications❗
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January 17, 2025 - May 2025 l Selection of the best student-topic pairs
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October 2025 l Start of second academic year DeMythif.AI
All applications must be submitted via the ADUM platform. Please read and follow the instructions carefully :
- Note the name of the thesis director, the doctoral school of the subject (in French), and the doctoral school (in French);
- At the bottom of the page obtained by clicking on the title of a doctorate, click on “ Candidate ”;
- This opens the “doctoral application area”.
- ” Log in to your account
- or “ Create an account ” if you haven't already done so
- Institution: select Université Paris-Saclay GS [Name of doctoral school in French], then Ecole Doctorale (in French) ;
- Fill in the diploma (if any) that will allow you to apply for a doctorate;
- Fill in another diploma ;
- Fill in other information;
- In particular, enter your level of English and French;
- The next step is to find your thesis subject, the easiest way being to use the name of your thesis supervisor. Please note that at this level, you are exposed to all thesis subjects, so make sure you select the one that belongs to the DeMythif.AI program;
- Fill in your motivation: start with “ This is an application to the DeMythif.AI program ”;
- Fill in any additional information (internships etc...) relevant to your application;
- Open your application form (containing all the information you have provided, as well as your thesis topic), sign it and send it to us.
- Create a one-page pdf document with the sentence “ Je soussigné(e), [PRÉNOM, NOM], déclare ne avoir séjourné pas en France plus d'un an entre le 18 janvier 2022 et le 17 janvier 2025 ” with your signature (this document is specifically required for this call) ;
- Build a PDF with all required information, up to 3 letters of reference (please ignore any indications for letters to be sent elsewhere);
- The application deadline for the DeMythif.AI program is Friday, January 17, 2025 at 23:59 CET, even if the specific PhD form mentions another deadline.
Please feel free to consult this web page in the weeks leading up to the closing date, as it may be enriched with answers to the most frequently asked questions.