Ingénieure/ingénieur de recherche - Post-Doc en Safety Management et statistiques

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 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 in a systematic way but based on ‘sensored’ parameters only. In other words, they 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. Indeed, 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 an event might be of interest to safety and is worth reporting is left to potential reporters and may vary from one individual to another as it may vary from one organization to another. Besides, the way an event is reported relies on the perception, understanding and analysis of the individual who reports and might differ from objective facts. Eventually, the database of reported events provides a partial a biased view of real operations. A major challenge to still use this data but for its actual value is to know more about the extent to which it represents operations.

The objective of this research is to explore through a combination of statistical and qualitative approaches the representativeness of the sample of the events reported to find ways to qualify the safety concerns it highlights and adjust the safety management strategy accordingly.

The statistical approach consists in determining a model to detect the occurrence of an event based on exhaustive sources of data such as PFR reports or time series.

The qualitative approach relying on interviews and surveys allows for getting insights on what lies behind the numbers, understand the motivations for and obstacles to sharing events with the aircraft manufacturer. It also drives a number of assumptions as to what type of events are worth investigating in priority through statistics, and allows for having grounded interpretations of the statistical results.

-        Knowledge and experience in machine learning

-        knowledge of machine learning language like R or Python

-        Quick learning

-        Self-reliance

-        Strong communication skills, ability to interact with people having diverse profiles and interests

-        Advanced spoken and written English

-        Interview and survey skills would be appreciated

-        Strong interest in research

-        Interest in aviation