Call for doctoral research projects co-supervised in Île-de-France Closed

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Status
Closed
Year
2022
Application deadline
15 April 2022 - 00:00
Results published on
21 April 2022 - 11:00

AI4IDF Presentation

Ile-de-France is home to the largest mathematical community in the world, several of the largest French computer science laboratories, and a dense industrial fabric in artificial intelligence. In this extremely rich context, the four main AI institutes - DATAIA, Hi! PARIS, PRAIRIE, and SCAI – have joined forces within the regional program DIM « AI4IDF » to structure and animate the community, and to provide industrial and international partners with a unified vision of the exceptional strengths present. The scientific program of the AI4IDF project aims to deepen knowledge in AI while keeping the human at the center of concerns. It is broken down into four axes: (1) Learning and optimization (2) NLP and dialogue with humans, (3) Robotics, movement and interaction with humans, (4) AI in human life: health, education and creation.

Submission of Applications

Applications must be submitted:

  • in PDF format only;
  • by email to the address {ai4idf_call_2022@inria.fr};
  • before May 17th 2022.

Each application must include:

  • the doctoral research project:

    • detailing the context, the scientific objective, the justification of the scientific approach as well as the relevance to AI4IDF themes,
    • written in English or French,
    • not exceeding 3 pages, single line spacing;

  • supervision specifying the role of each supervisor;

  • the institutes of the co-supervisors;

  • the candidate's CV;

  • the chosen doctoral school for enrollment in the thesis in case of successful application.

Project Selection

Eligibility of proposals:

  • The proposed topics should be co-supervised:

    • either between two of the four institutes DATAIA, Hi! PARIS, PRAIRIE, and SCAI,
    • or between one of the four institutes DATAIA, Hi! PARIS, PRAIRIE, SCAI, and a laboratory or research unit from Ile-de-France outside these institutes.

  • Approval from the doctoral school mentioned in the application in case of selection.

The selection committee is made up of 8 scientists with complementary skills in order to provide expertise on the entire scientific program of the project. It is composed half of members from the project's institutions and organizations, and half of external French or foreign members recognized for their skills in artificial intelligence.

The members of the selection committee will be asked to evaluate projects on which they have no conflict of interest.

The evaluation criteria are as follows:

  • excellence of the subject and relevance in view of the scientific program of DIM AI4IDF;

  • excellence of the candidate's profile and adequacy of the profile to the project, motivation to join the program;

  • proposed international and/or industrial mobility;

  • clarity of the envisaged work program.

Communication of results: {{ release }}

AI4IDF Scientific Program

The research program is structured around four major axes, each corresponding to major current challenges aimed at best integrating AI into the human environment, to improve existence.

Axis 1 – Learning and optimization: between algorithmic efficiency and theoretical guarantees

A large part of recent advances in artificial intelligence, notably in artificial vision and natural language processing, have been achieved using machine learning algorithms and in particular large-scale optimization. If successful implementation of learning in these areas requires « job » expertise (physics of image formation, linguistics) and methods adapted to the corresponding constraints (cf. axes 2 and 3 below), we can identify common scientific questions to all fields of AI impacted by learning and requiring the combination of new mathematical and computer approaches to be effectively addressed and solved. These constitute the core of the « learning and optimization » axis, with three main themes.

  • Axis 1.1 Deep learning theory.
  • Axis 1.2 Optimal use of resources.
  • Axis 1.3 Beyond pattern recognition: weak supervision, structured learning, reinforcement learning.

Axis 2 – NLP and dialogue with humans

The second research axis will focus on the fields of AI related to language, and will notably involve natural language processing (NLP) and human-machine dialogue (conversational agents, etc.). It will be organized around four major themes, strongly interacting with each other.

  • Axis 2.1 Large-scale language models.
  • Axis 2.2 Information extraction and text mining.
  • Axis 2.3 Controlled generation.
  • Axis 2.4 Transmodal and multimodal tasks.

Axis 3 - Robotics, movement and interaction with humans

For robotics to meet its promises and achieve expected socio-economic objectives, significant scientific advances remain to be made. They will require both "material" experimental platforms benefiting from the latest progress obtained in mechatronics and sensor technology and "intelligence" software obtained thanks to fundamental progress in several key areas of AI.

  • Axis 3.1 Statistical learning and optimal control.
  • Axis 3.2 Perception.
  • Axis 3.3 Planning.
  • Axis 3.4 Robotics interacting with humans.

Axis 4 - AI in human life: examples from health, education, and creation

AI has also, through its diffusion as a widely used technique, profoundly modified many other disciplines whose impact in human daily life is tangible. We will develop these impacts through three application areas permeating various aspects of society.

  • Axis 4.1. Health example.
  • Axis 4.2. Education example.
  • Axis 4.3. Creation example.