Ingénieur de recherche

# Ingénieure/Ingénieur de recherche en Safety Management et statistiques* Toulouse, 31400* CDD* 01/03/2026- 28/02/2029## DescriptionL’ENAC, École Nationale de l’Aviation Civile, est la plus importante des Grandes Écoles ou universités aéronautiques en Europe. Elle forme à un spectre large de métiers : des ingénieurs ou des professionnels de haut niveau capables de concevoir et faire évoluer les systèmes aéronautiques et plus largement ceux du transport aérien ainsi que des pilotes de ligne, des contrôleurs aériens ou encore des techniciens aéronautiques.Ses laboratoires de recherche sont à la pointe de l’innovation et travaillent activement en coopération avec des universités internationales de haut niveau pour un transport aérien toujours plus sûr, efficace et durable.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.*Pour soutenir sa dynamique en faveur de la promotion de la diversité, l’ENAC facilite l’accueil et l’intégration des travailleurs en situation de handicap.*In a so-called ultra-safe industry like aviation, it is now widely acknowledged that relying on accidents to enhance safety is not sufficient. In order to have access to feedback from operations, including less critical situations than accidents or significant incidents, reporting systems have been introduced in aviation at several levels, leading to databases of spontaneously reported events that might be of interest from a safety viewpoint. ECCAIRS and ASRS are examples of such databases at regional level in respectively Europe and North America. In addition to these regional initiatives, a number of aviation organizations such as manufacturers or airlines have their own internal reporting systems allowing them to collect events considered safety relevant by the reporter. These reports constitute a unique source of qualitative information on operations that are nowhere else available. They might come in addition to FDM data or other sources of structured data collected during flights in a systematic way that are based on ‘sensored’ parameters only. In other words, these reports are a very valuable source of information to develop insights on the safety of operations overall. However, the events reported through these channels do not provide a complete and accurate picture of real operations for several reasons. First of all, reporting is not mandatory for events that are not critical enough to fall under the ICAO Annex 13 or other mandatory reporting scopes (e.G. EASA regulations or national/regional laws). Therefore, the appreciation of whether such events might be worth reporting is left to potential reporters and may vary from one individual to another or one organization to another. Second of all, the way an event is reported relies on the perception, understanding and analysis of the individual who reports it and is, in that sense, a limited interpretation of objectives facts. Eventually, this causes the databases of reported events to present a partial and biased view of real operations. If we want to use this data wisely and recognize its actual value we need to tackle a major challenge: explore to what extent it is representative of all operations.**About the role**:You will contribute to exploring the representativeness of the safety events reported by airlines by joining the ENAC-Airbus “Safety Management” research program. This program was created in 2018 and renewed in 2023. It takes place at ENAC where a small team of research engineers and post-doctoral researchers are currently exploring different research topics related to emerging aviation safety challenges. As for you, you will more specifically work in tandem with a research engineer to investigate the topic of shared events representativeness from different perspectives. The approach currently adopted ranges from interviewing airlines representatives about their practices, to data analysis and statistics.**Key activities:**- Identification, cleaning, processing and analysis of large and complex datasets as well as developing machine learning models with statistical methods and optimization techniques- Regular interactions and activities with Safety experts- Interviews and surveys of safety experts## Profil-
Master’s or PhD in Data Science or Statistics or Computer Science or Aerospace Engineering or any related field-
Strong proficiency in Python or similar programming languages for data analysis and machine learning-
Solid knowledge and experience with machine learning models/frameworks and statistics-
Ability to work with people from diverse backgrounds (pilots, researchers, safety analysts…)-
Great flexibility, autonomy and pro-activity-
Fluency in written and spoken English-
Interest in research-
Interest in aviation#J-18808-Ljbffr