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Project manager

    Description

    Créée il y a 70 ans, l’ENAC, École Nationale de l’Aviation Civile, est la plus importante des Grandes Écoles ou universités aéronautiques en Europe. Elle assure la formation initiale et le perfectionnement des cadres et des principaux acteurs de l’aviation civile : ingénierie, navigation aérienne, pilotage, gestion aéroportuaire, recherche, expertises, développement à l’international.

    L’ENAC est un établissement public à caractère scientifique, culturel et professionnel – grand établissement (EPSCP-GE), sous tutelle de la DGAC (Direction Générale de l’Aviation Civile), Direction du Ministère de la Transition Écologique et Solidaire. L’ENAC comprend une direction générale localisée à Toulouse et 8 sites en France.

     

    Mission

    The CODA project involves developing a system in which hybrid human-machine teams collaboratively perform tasks.

    To do so, the system put together state of art from different fields:

    i)                Prediction models to foresee future situations and have the system know which activities will be carried out by the operators and their impact on the same human performance.

    ii)              Neurophysiological assessment of mental states to enable the system to know operators’ real current level of workload, attention, stress, fatigue, and vigilance by validating the predicted cognitive models and maximizing the effectiveness of the interaction between the human and the machine by developing an HMPE (human machine performance envelop).

    iii)              AI-based adaptable and explainable systems, to have the system act to prevent future performance or safety issues.

     

     

    Remote digital towers (RDT) are taking place around the world to ensure efficiency and safety. TRUSTY harnesses the power of artificial intelligence (AI) to enhance resilience, capacity, and efficiency in making significant advancements in the deployment of digital towers. The overall goal of TRUSTY is to provide adaptation in the level of transparency and explanation to enhance the trustworthiness of AI-powered decisions in the context of RDT. Through the video transmission data from RDT, TRUSTY considers the following major tasks:

     

    1. Taxiway monitoring (i.e., bird hazard, presence of a drone, autonomous vehicle monitoring, human intrusion, etc.).

    2. Runway monitoring (approach and landing) misalignment warning and the corresponding explanation.

     

    To deliver trustworthiness in an AI-powered intelligent system several approaches are considered:

    •        ‘Self-explainable and Self-learning’ system for critical decision-making.

    •        ‘Transparent ML’ models incorporating interpretability, fairness, and accountability.

    •        ‘Interactive data visualization and HMI dashboard’ for smart and efficient decision support.

    •        ‘Adaptive level of explanation’ regarding the user's cognitive state.

    •        “Human-centric AI” enhances the trustworthiness of AI-powered systems.

    •        “Human-AI teaming” to consider users’ feedback to ensure some computation flexibility and the users’ acceptability.

     

    The candidate will integrate the research group headed by Prof Christophe Hurter with the core research area on Explainable AI (XAI) and data visualization. The candidate will lead and synchronize the two projects with the involved partners (France, Italia, Sweden, Spain).

     

    Profil

    Requirements:

    • experience in leading scientific research and managing collaborative scientific projects.

    • a high degree of independence, commitment, flexibility, and team spirit.

    • very good command of the English language.

    • Academic level: Master university degree, engineer degree, or PhD degree in a subject relevant to the domains of the computer science, Artificial intelligence and/or data visualization

    • Travels: mostly in Europe, possibly worldwide

    • Starting date: 01/09/2024

    • Duration: 18 months