A 6-month Master internship, ideally starting in March 2026, is available at the Institut de Génétique Fonctionnelle de Lyon (IGFL, ENS de Lyon), within the Spatial-Cell-ID facility. The project contributes to the development of a full 3D MERFISH imaging and analysis pipeline dedicated to high-resolution spatial transcriptomics.
The internship focuses on two main objectives. The first is the design and implementation of a napari-based visualization tool enabling efficient inspection of large 3D MERFISH datasets stored in a Zarr-based datastore. This plugin will support quality control, method development, and integration with our existing Python processing framework. The second objective concerns the improvement of 3D cell segmentation methods. The work will involve adapting recent 2D deep-learning approaches such as RNA2Seg to volumetric data, adapting model architectures, training and validating on experimental datasets, and optimizing performance and robustness for large-scale analyses.
The position is suited for a highly motivated M2 or engineering student with a background or strong interest in image processing, computer vision, deep learning, or applied mathematics. Familiarity with Python is appreciated, and the internship will provide training in software development, deep learning, and spatial transcriptomic imaging. The student will join an interdisciplinary team and contribute directly to ongoing open-source developments.
To apply for this job email your details to hugo.blanc@ens-lyon.fr