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    Inria

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    PhD Position F/M Learning and Equilibrium Engineering for Frugal Data Markets

    Lille, FranceOn-SiteFull-timePosted 1w ago
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    Job description

    PhD Position F/M Learning and Equilibrium Engineering for Frugal Data Markets

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    Contract type : Fixed-term contract

    Level of qualifications required : Graduate degree or equivalent

    Fonction : PhD Position

    About the research centre or Inria department

    Created in 2008, the Inria center at the University of Lille employs 360 people, including 305 scientists in 16 research teams. Recognized for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria center at the University of Lille maintains a close relationship with large companies and SMEs. By fostering synergies between researchers and industry, Inria contributes to the transfer of skills and expertise in the field of digital technologies, and provides access to the best of European and international research for the benefit of innovation and businesses, particularly in the region.

    For over 10 years, the Inria center at the University of Lille has been at the heart of Lille's university and scientific ecosystem, as well as at the heart of Frenchtech, with a technology showroom based on avenue de Bretagne in Lille, on the EuraTechnologies site of economic excellence dedicated to information and communication technologies (ICT).

    Context

    The growing development of digital services and artificial intelligence relies on increasingly large volumes of data. Data markets provide a promising framework for enabling decentralized actors to share, exchange, and exploit data while creating economic incentives for data production and sharing. However, current data-driven systems often rely on intensive data collection, communication, storage, and computation, raising important questions about their environmental footprint.

    Designing frugal data markets therefore requires going beyond the classical objectives of efficiency and individual utility. Agents should be able to strategically decide what data to collect, share, acquire, or process, while taking into account the associated economic and environmental costs. These decisions are inherently interdependent: the value of information depends on what other agents know and do, while individual decisions affect both the information available to the system and its overall resource consumption.

    This PhD thesis will investigate the interplay between strategic information, learning, equilibrium formation, and frugality in decentralized data markets. Building on game theory and multi-agent learning, the objective is to develop models and methods that explain and control how strategic agents learn and interact in data markets, and how their collective behavior can be steered towards equilibria that achieve desirable trade-offs between economic value, information quality, and resource consumption.

    This PhD thesis is part of the PEPR NumEco research program, dedicated to the development of a more frugal and sustainable digital ecosystem.

    Assignment

    The first objective is to develop game-theoretic models of decentralized data markets in which agents strategically decide how much information to acquire, share, or exploit. The models will explicitly account for the costs associated with data collection, communication, storage, and processing, as well as the value generated by the resulting information.

    The second objective is to study learning and equilibrium formation in these markets. Agents may have incomplete or asymmetric information about other participants, the value of data, or the state of the system. The thesis will investigate how learning dynamics and strategic information exchange affect the equilibria that emerge, and under which conditions decentralized learning leads to efficient or frugal outcomes.

    The third objective is to develop equilibrium-engineering mechanisms for frugal data markets. Rather than taking the resulting equilibrium as given, the thesis will explore how incentives, information structures, pricing mechanisms, and learning objectives can be designed to steer strategic agents towards equilibria that jointly balance data value and resource consumption. This will include studying the trade-offs between the benefits of additional information and the environmental cost of acquiring and processing it.

    Finally, the thesis will investigate how these mechanisms can be implemented through multi-agent learning algorithms, combining game-theoretic equilibrium concepts with reinforcement learning, no-regret learning, and equilibrium-seeking methods. Particular attention will be paid to settings where agents learn from limited information and where the learning process itself contributes to the overall computational and communication footprint.

    Main activities

    The thesis is expected to contribute:

    • new game-theoretic models for decentralized and strategic data markets incorporating economic and environmental costs;
    • theoretical results on equilibrium formation and selection under incomplete information and learning;
    • learning and equilibrium-seeking algorithms for frugal multi-agent systems;
    • incentive, pricing, and information-design mechanisms for engineering equilibria that balance data value and resource consumption;
    • quantitative measures and trade-offs between information value, strategic performance, and digital resource consumption;
    • experimental validation on representative data-market scenarios.

    The overarching objective is to establish game-theoretic and learning-based foundations for frugal data markets, where agents do not simply optimize the value generated from data, but collectively learn to determine which information is worth acquiring, sharing, and processing given its economic and environmental cost.

    Skills

    Required skills: game theory, optimization, and multi-agent learning; a strong background in applied mathematics and an interest in frugal digital systems and data markets.

    Benefits package

    • Subsidized meals
    • Partial reimbursement of public transport costs
    • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
    • Possibility of teleworking and flexible organization of working hours
    • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
    • Social, cultural and sports events and activities
    • Access to vocational training
    • Social security coverage

    Remuneration

    €2,300 gross per month

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    General Information

    • Theme/Domain : Optimization, machine learning and statistical methods
      Statistics (Big data) (BAP E)
    • Town/city : Villeneuve d'Ascq
    • Inria Center : Centre Inria de l'Université de Lille
    • Starting date : 2027-01-01
    • Duration of contract : 3 years
    • Deadline to apply : 2026-10-02

    Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed.

    Instruction to apply

    Please provide your CV and cover letter.

    Defence Security :
    This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment.

    Recruitment Policy :
    As part of its diversity policy, all Inria positions are accessible to people with disabilities.

    Contacts

    • Inria Team : INOCS
    • PhD Supervisor :
      Le Cadre Helene / [email protected]

    About Inria

    Inria, the French national institute for research in digital science and technology, supports the French government in national research and innovation strategies in the digital field, acting as Digital Programs Agency. Inria leads over 300 research and innovation projects with its 3,500 scientists, engineers, and support staff, in partnership with universities and the digital ecosystem (businesses, entrepreneurs, and public stakeholders). Together, we explore strategic fields such as artificial intelligence, cybersecurity, quantum computing, cloud technologies, digital transformation in healthcare, digital twins, and digital technologies for defence. We develop practical solutions such as software, tech startups, partnerships with national companies, and cutting-edge training programmes. Our goal is to drive scientific, technological, and industrial excellence to ensure France’s digital sovereignty.

    Job details are sourced from the employer's original posting.

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    About the company

    Inria

    INRIA is the French national research institute for digital science and technology.

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