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Research Fellow in ”Drones and Artificial Intelligence: security and autonomous services”

ABG-135837 Emploi Niveau d'expérience indifférent
20/02/2026 Statutaire de la fonction publique > 35 et < 45 K€ brut annuel
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Université Gustave Eiffel - Campus de Lille
Villeneuve d'Ascq - Les Hauts de France - France
Mathématiques
  • Sciences de l’ingénieur
  • Télécommunications
Multimodal data analysis, innovative AI architectures, edge computing, federated learning
Recherche et Développement

Employeur

Université Gustave Eiffel is a major French public research university dedicated to sustainable cities, mobility, infrastructure and complex systems. It combines academic excellence with applied research addressing key societal and technological challenges.

The position is hosted within the COSYS Department (Components and Systems), at the LEOST laboratory (Lille campus). The research environment is interdisciplinary, bringing together expertise in applied mathematics, artificial intelligence, signal processing, wireless communications and cybersecurity. The laboratory maintains strong national and European collaborations and offers a dynamic, research-intensive environment.

Poste et missions

The successful candidate will develop innovative research in Applied Mathematics and Artificial Intelligence for complex, dynamic and data-intensive systems.

Research activities will include:

  • Mathematical modelling and statistical learning for heterogeneous and multimodal data,
  • Design of advanced machine learning architectures adapted to constrained or distributed environments (edge computing, federated learning),
  • Development of robust and reliable AI methods for dynamic and non-stationary contexts,
  • Contribution to cybersecurity challenges in communicating systems, including drone detection and protection.

The researcher will actively contribute to the scientific life of the laboratory through high-level publications, supervision of PhD students, participation in national and European research projects, and development of academic and industrial partnerships.

Mobilité géographique :

Internationale

Télétravail :

Partiel
Possible sur demande, 3 jours / semaine de présence obligatoire

Profil

  • PhD in Applied Mathematics, Statistics, Machine Learning, Computer Science, or a closely related field,
  • Strong expertise in mathematical modelling, optimization, statistical learning, or deep learning,
  • Ability to connect theoretical developments with real-world system constraints,
  • Proven track record of high-quality scientific publications,
  • Demonstrated capacity for interdisciplinary collaboration.

Experience or interest in signal processing, wireless communication systems, or cybersecurity of communicating systems will be considered an asset but is not mandatory.

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