Student M1 or M2 internship in atmospheric sciences

Are you keen to undertake your MSc project via an internship in the area in the atmospheric sciences?
:point_right: You might want to check this offer at IMT Nord Europe

Required profile:
The internship subject is aimed at an M1 or M2 student with a solid basis in atmospheric sciences (physico-chemistry), as well as skills in scientific programming. Knowledge of aerosol particles, their physical properties and detection would be an asset.

The internship start date is expected between February and April 2024 and shall last for 6 months.

The objective of this M2 internship is to study the dynamics of BrC from forest fire events using both in-situ and photometer solar data. The influence of wildfire emissions in the database between 2016 and 2023 will be identified using the in-situ ATOLL data and back-trajectory model outputs. The ATSR World Fire Atlas forest fire inventory could also be coupled to backtrajectory outputs and in-situ observations. These events will create a database of physical properties of the in-situ and remote sensing (single spectral diffusion albedo, particle size, etc.) characteristics associated with forest fire emissions. After this pilot analysis in Lille, the method can be extended to other sites (e.g., SIRTA, in Paris), as well as other types of measurements (LIDAR).

The first part of the internship will be devoted to familiarizing with the topic, the field and atmospheric data processing. The second part will aim to develop and validate a code based on the INTERPLAY algorithm, making it possible to identify forest fire transport events at the measurement site based on a multi-year dataset. The third part will consist of studying the BrC component of aerosols, particularly according to source regions and since emission.

The intern will be part of an ambitious project and an international research framework, in particular the “Atmosphere Observing System” satellite mission (, as well as the RI ACTRIS ( He/she will acquire advanced skills in processing atmospheric data, in the context of understanding the effects of climate change, particularly in view of the increase in the frequency and intensity of forest fires.