ML-News: M2 Internship at ICube, Strasbourg, France – Unsupervised Bacterial Movement Analysis

Join ICube’s M2 internship in Strasbourg, France to unsupervisedly characterize bacterial movement for real-time pathogen detection using optical imaging and machine learning.

ICube in Strasbourg, France is offering an M2 internship focused on unsupervised characterization of bacterial movement using mini-microscope videos. The project, known as LAIveBactDetect, aims to develop a real-time, integrated screening method for pathogens using optical imaging, video-based object detection, tracking, and machine learning classification. This internship will specifically delve into enhancing current analysis techniques by studying individual and group bacterial movement. The intern will apply unsupervised learning methods to identify trends from bacterial movement data and determine if the system can identify unknown bacterial types.

The ideal candidate is a Master’s (M2) or final-year engineering student specializing in Computer Science or Image Processing with strong programming and machine learning skills. Familiarity with Python (pandas, scikit-learn, PyTorch, TensorFlow, Keras) and Git is required. The internship lasts for 6 months and is located at ICube Lab, Illkirch Campus near Strasbourg, France. For more information, contact Joseph Lam at jlam[at]unistra.fr.

Tags: M2 internship, ICube, Strasbourg, France, unsupervised characterization, bacterial movement, LAIveBactDetect, optical imaging, video-based object detection, machine learning classification, unsupervised learning methods