The doctoral school
The STIC Doctoral School covers a unique thematic continuum in France in the domain of digital technology and science: control, signal processing, image processing, robotics, networks, telecommunications, data science, machine learning and artificial intelligence, human-machine interactions, programming, algorithmics, languages and architecture.
The STIC DS offers original research projects combing theory and experimentation. These projects cover a wide range of application fields: e-science, aeronautics and space, transportation, autonomous vehicles, security, smart home, internet of things, energy; e-learning, biotechnology and health, etc.
The STIC DS offers a diverse research environment in renowned research units within the Paris-Saclay University and national resarch organisms.
Moreover, numerous companies host PhD students in their laboratories or R&D departments (on a CIFRE contract or temporary employment contract basis).
The STIC DS operates in a highly dynamic environment and works on innovative and cross-cutting STIC multidisciplinary projects e.g. in Mathematics, Engineering, Mechanics and Materials, Biology, Human and Social Sciences, Movement Sciences, etc.
Organization of the site
The STIC doctoral school is organized in 4 scientific programs called "pôles". These programs are introduced here through key words and a short description.
If you wish to reach the person in charge of a specific pôle, please visit the contact page.
Pôle 1 : Systems & Control, Signal Processing, Images Processing, Robotics
- systems and control : modelling, identification, analysis, control, estimation, optimization
- mathematical processing of information, signal and images
- new generation of innovative and interactive robotic systems: structure, actuation and control
- signals and systems modelling
Aeronautics and space, transportation systems, energy, biotechnology and life sciences, social and cultural life, public media, security,... all these sectors, and many others, require fundamental research in systems and control theory, information, signal and image processing and robotics and require the development of complex numerical models.
Systems and control theory allows the analysis, understanding and mastership of the dynamic behaviour of complex systems in extremely varied fields. They lead to the design of smart devices that can detect, communicate, evolve and act on the environment, via many controllers and sensors. These systems give rise to various models: multi-physics, multi-scale (w.r.t. time or space), hybrid, discrete events… and allow to predict the behaviour and to better understand and push the limits of achievable performance in the presence of disturbances and modelling uncertainties.
Information, signal and images mathematical processing studies, models and corrects alterations or modifications that affect the transmission of information, which may admit different representations (continuous, discrete, parametric, etc.). These treatments seek to recover the original information or to improve its quality, which often results in solving inverse problems. They also aim to extract structural information and interpret the contents, for example by using pattern recognition, machine learning and artificial intelligence. Specific problems are given by the temporal, spatial or spatio-temporal dependencies of these information flows. Mathematics play a fundamental role, particularly through probability and statistics, numerical analysis, optimization, information theory, variational methods, etc.
Robotics aims to provide sensory, motor and cognitive capacities to artificial systems that can be virtual or physical, and to be created. A robot perceives, acts, decides, learns, in a complex dynamic environment, structured or not, that can be shared with humans and/or other robots. The aim is to design a new generation of innovative robotic systems concerning their structure, actuation and control.
At the confluence of these scientific and application areas, development and exploitation of digital tools in systems generating or processing information is a major issue. It involves building and implementing mathematical models of various nature (deterministic or stochastic, continuous or discrete) for the modelling of signals and systems. Numerous challenges are to be faced: develop techniques and specific mathematical methods, build, validate and analyze efficient algorithms, connect models from different physical domains, of different scales, make them interact as well as with the human who exploits them, integrate the models in decision making, in optimization or inversion processes, going up to implementation within specific software and hardware architectures. The evolution of computing power and automatic optimization/parallelization tools allows to consider a rapid acceleration of the TRLs (Technology Readiness Level) of algorithmic codes designed in laboratories to innovative SMEs and industrial companies.
Pôle (2) : Networks, Information and Communications
- Internet architecture and cloud services
- Network architecture, design, programmability and security
- Fixed and mobile network implementation, core and edge technologies, terminals,
- Information and communication theory, metrology, methods and tools for network simulation and operation
The "Networks, Information and Communications" pole covers the whole stack of protocol layers involved in the design and optimization of communications networks, as well as their use towards the development of services.
The research carried out addresses network basics and theories, allowing the establishment of fundamental limits or the elaboration of new algorithms intended to increase the capacity, the efficiency, the security and the overall performance of the communication network. It takes into account the allocation of resources, the architectural, protocol and global constraints and is pursued down to the development of advanced engineering tools for performance evaluation of networks, their optimization and their deployment.
The pole also addresses the implementation and the physical specificities of sub-systems, core and access networks technologies, including terminals and the associated signal processing. This concerns all networks, whether they are based on wirelines, on optical fibres and optical devices, on radio and antenna systems, or on their combination.
Software defined networking and the related methods to access and to exploit cloud resources by network devices or by end users are also a major part of pole 2 activities.
Finally, the pole places its scientific vision in the context of the wide and increasing penetration of networks in the private and professional spheres and, as such, is also broadly concerned by the development of services, provided they are inherently based on, and accordingly parameterized by, specific network resources.
Pôle 3 : Big Data, Knowledge, Machine Learning, and interactions
- big data and knowledge management, reasoning
- natural language processing
- data mining, statistical learning
- interaction, visualisation and virtual reality
The pôle ``Data, Knowledge, Machine Learning, and interactions'' focusses on the scientific issues related to the science of data (Data Science), and to the various modes of communication with a machine, whatever the type of machine or interaction environment. In order to understand, process and use massive data and knowledge, it is necessary to develop automatic learning methods and symbolic approaches related to artificial intelligence.
The pôle covers most of the topics addressed by the Datasense working group of the Labex Digicosme. Pôle 2 research activities have a large spectrum of applications, they frequently requires multidisciplinary expertises, for instance in interaction with Mathematics, with Humanities and Social Sciences.
Scientific key words of the pôle:
- Big Data, heterogeneous, semi-structured, distributed data: Web, social networks, sensor data
- Knowledge: representation, reasoning, logic, and more generally questions related to the artificial intelligence, Semantic Web.
- Interactions between humans and machines, robots, new objects: virtual and augmented reality, interactive robotics
- Natural language processing (search and retrieval of information, translation, ...): multimedia (speech, writing, sign language) and multilingual aspects are at the heart of our studies
- Statistical learning: defines a programming paradigm based on examples and interaction with the environment, as opposed to specification-based programming.
Pôle 4 : Models, Algorithms, Languages and Architecture for Programming:
Operational research, optimization
Programming, software engineering, verification
Algorithmic, formal computation, graphic computing, cryptography
Architecture, distributed computing and services, high performance computing
Hardware and software design of computer systems
The "Programming: Models, Algorithms, Languages, Architectures" pôle aims to bring together the sciences of software, from the study of computational models to the efficient execution of programs on various architectures. The study of the models is discrete or continuous: Algorithmic, ie the design of effective methods of resolution; the study of programming languages, their semantics; the design of computer programs, their modularity, testing and verification to ensure safe and secure operation; execution environments as well as the different hardware architectures.
This cluster covers the research activities of Scilex working of the Labex Digicosme. The research in algorithmics and optimization in particular have a large number of applications including applications in the following disciplines: bioinformatics, energy, transport and telecommunication networks.
- Logic, algorithmics, combinatorics, formal computation, graphic computing, coding, cryptography
- Operational research, optimization, game theory, decision support
- Programming, software engineering, verification, proof, testing, operational safety
- Distributed architecture, compilation, computing and services, high performance computing
- Hardware and software design of computer systems, embedded software
Governance and Rules
This is a trial.
PhD Student Recruiting Process (English presentation)
Warning: This page contains an overview of the ED STIC recrutement process. It contains references to specific pages for practical aspects.
Recruting PhD student follows two differents tracks:
- a competition is organized for recruting PhD student funded by the partner institutions or by specific funding such as Labex DigiCosme or Digiteo
- individual recrutement related to PhD funding such as AMN, ANR, CIFRE, CSC and others
The recruting process is similar in both cases and consists of the following steps:
- thesis project submition by a supervisor
- approval of the project by the director of the lab
- approval of the project by the doctoral school
- student application on a thesis project
- review and evaluation of the student application by the supervisor
- review and evaluation of the student application by the doctoral school
For the competition and also for others kinds of funding offers, strict deadlines have to be respected. Please visit the Concours & AAPs web page.
In both cases (competition or individual), the thesis project must be submitted by the supervisor through Adum.
If you wish to submit a PhD project, practical details are provided here.
After checking the adequacy of the PhD project with the cluster scientific domain, the research lab director's opinion is collected as well as that of a member of the cluster committee. After validation, the project is publish for application.
Use the links given by the PhD Thesis Projects web page to get the relevant list of PhD topics.
The applicant submits her application on a project using Adum. The application needs to be prepared by a contact with the project supervisor and, in case of a positive answer, by an appointment with him/her.
In order to apply on a project, use the links given by the PhD Thesis Projects web page to access to the relevant project. At the end of the presentation, you'll find a "apply" icon that you should use for that purpose. The application web page provides details about the contents of the application file
In both cases (competition or individual), an interview is organized. The interview aims to ensure that the candidate's profile is in line with the project, to evaluate the candidate's motivation for the project and for research in general. The interview provides also the opportunity to inform the applicant about the PhD thesis processes like doctoral education and follow-up.
- A student or applicant may apply on at most two projects and should express his/her priority between the two.
- A supervisor can support at most two candidates with the following restrictions :
- at most two candidates as supervisor
- at most two candidates as co-supervisor
An application concerning a project eligible for several fundings accounts for one application.