Annual PhD Funding Campaign

  • Digital and Social Sciences
  • Digital and the Environment
  • Applied quantum technologies (quantum computing, quantum simulation, quantum communication or quantum metrologies and sensing), in partnership with QuantEdu-France through QuantAzur Institute for which transdisciplinary projects involving several laboratories will be particularly appreciated.
Why should you apply as a PhD candidate?
How to apply?
As a PhD candidate

Application deadline: 2024 May, 6th

To apply:

  • Simply click on the topic of your choice in the list below and click on the "Candidater/Apply" button at the bottom of the topic page
  • In any case, send an e-mail to the PhD supervisor to inform him or her that you apply.

The director will then select the student (s)he will support, prepare the application file and the audition with him/her, and submit the application file to DS4H Graduate school.

If you are selected, you will have to register to the doctoral school corresponding to your subject:

As a PhD supervisor

Application deadline: 2024 May, 6th

PhD supervisors apply for DS4H fundings after having selected a PhD candidate on a PhD given topic.

Folders submitted by the potential PhD supervisors should contain :

  • A description of the chosen PhD subject
  • The candidate’s CV 
  • Letter of motivation from the candidate
  • If the master is still in progress: the transcripts of at least Master 1 and the first semester of Master 2 (or equivalent) with, if available, the rankings among the master, and a scientific description of the current research internship
  • Else: the Master diploma, a complete transcript of the Master 2 or equivalent, and the dissertation with at least a summary in French or English
  • A letter of the potential PhD supervisor with commitment to supervise the candidate, a description of the knowledge (s)he has of the candidate, and why (s)he chose this candidate on this subject
  • Optionally : recommendation letters and any document likely to support the quality of the triplet

How to submit a PhD subject?

Before May, 6th

  • Conditions: please refer to the e-mail from Gilles Bernot, dated March 12th.

An additional allowance of 10 K€ will be allocated by DS4H Graduate school to selected subjects submitted before April, 10th.

Selection Process
2024 Campaign Calendar
  • April 10th: Deadline for submission of thesis topics that will be widely circulated internationally and benefit from 10k€ additional allowance
  • May 6th: Deadline for submission of thesis topics and applications
  • May 10th: Final choice of student supported by each thesis director
  • Mid-May to mid-June: Audition of the students and their potential thesis directors by the rapporteurs
  • June 11th: Indicative ranking by the jury from the DS4H Graduate school COSP
  • June 14th: Final laureates decision by the DS4H Graduate school Steering Committee
What if the PhD of your dream is not on this list? or if you want to apply after the official closing of the campaign?

You can still contact your doctoral school directly to identify open thesis subjects and fundings:

You can also identify the researcher of DS4H Graduate school's partner laboratories best matching your subject of interest and ask him/her if he/she would be willing to supervise you and if he/she can submit a specific topic for you.
Former Laureates

Since 2019, DS4H Graduate school has been awarding research grants targeting thematic priorities:

  • Digital and Social Sciences
  • Digital and the Environment
  • Artificial Intelligence, in partnership with the 3IA Côte d’Azur
  • And more recently, applied quantum technologies (quantum computing, quantum simulation, quantum communication or quantum metrologies and sensing), in partnership with QuantEdu-France through QuantAzur Institute


Discover below the 2024 doctoral projects. This list wil be updated on a regular basis until 2024 May, 6th.
Last update: 2024 April 11th

Decentralized machine learning JL Lagrange / i3S
Self-supervised learning for histological image analysis Inria MORPHEME
Synaptic Delay Learning For Spatiotemporal Pattern Recognition i3S
Parameter learning for probabilistic biological neural networks i3S
Optimal Management of Green Data Centers i3S
Identification of factors influencing the rate of progression of ALS using supervised learning techniques i3S
Integrating cellular automata and explainable AI for modeling complex systems i3S
Multiple Optimizations in Satellite-Aerial-Terrestrial Networks (SATN) i3S
Machine Learning Solutions for Quantum Internet i3S
Knowledge graph embedding models: symbolic knowledge injection and discovery i3S
Formal modelling of cell metabolism under the influence of carcinogenic molecules i3S
Efficient Scaling of event queues based MicroServices Graphs i3S
Program recognition with artificial intelligence i3S
Energy efficient slicing for 6G networks using AI/ML technics i3S
On the convergence of iterative sampling methods and the detection of meta-stable states in protein science Inria ABS
Mining protein dynamics with transformers Inria ABS
Problem Size Generalization in Neural Combinatorial Optimization Inria COATI
Energy-efficient QoE-aware Beyond 5G Future Mobile Networks Inria DIANA
Extension of the Conklin nomenclature: how to name cells in ascidian embryo? Inria MORPHEME
Generalization Capabilities of Machine Learning Algorithms Inria NEO
Federated Reinforcement Learning Inria NEO
(Semi)Decentralized Digital Currencies and Mutable Smart Contracts for Permissioned Blockchains Distributed Ledgers for the European Area Inria SAM
A theory of primitive signals Inria SAM
Overlay network for distributed IoT Inria SAM
Compiling Dynamic Languages to WebAssembly Inria SPLITS
Predictive Debugging of Synchronous Reactive Languages Inria SPLITS
Optimistic Gradual Typing for TypeScript Inria SPLITS
Efficient data structures and algorithms for processing massive point clouds Inria TITANE
Decentralized coordination of intelligent processes to improve the quality of a collection of knowledge graphs Inria/i3S WIMMICS
Classification of macro-reentrant atrial tachyarrhythmias using multimodal surface and endocardial data: Contribution of machine learning and signal processing. i3S
Development of a Framework for Design and Analysis of Neural-network-based Controllers, Application to Autonomous Vehicles i3S
Decentralized estimation and distributed control for a formation of autonomous surface and underwater vehicles i3S
Novel tensor decompositions for atrial fibrillation analysis i3S
Quantum algorithms for vision-based robot localisation Inria ACENTAURI
Optimal control of competition within microbial communities Inria BIOCORE
Exploring and exploiting the new capabilities of room temperature MEG sensors Inria CRONOS
Modeling of cortical evoked potentials by direct stimulation and their link to electromyography Inria CRONOS
Deep Learning Methods for Understanding Psychiatric Interviews Inria STARS
Design for Smart and Integrated Antenna for CubeSat LEAT
Design of networks and reconfigurable intelligent surfaces based on liquid metal LEAT
Dual numerical and experimental characterization of individual exposure to RF according to realistic uses LEAT
Modeling and Estimation of Creative Strategies in Problem Solving (CreaStra) LINE
Fine-grained analysis of emotions and human behavior based on multi-sensor fusion GREDEG