This internship focuses on improving an existing pipeline for generating a synthetic bronchoscopy dataset. The work involves refining the generation of 3D trajectories and corresponding camera orientations, as well as enhancing the rendering realism to create a realistic dataset that can be used for AI-based navigation systems. Context: Early detection of lung cancer significantly reduces mortality. After a suspicious lesion is detected via Computed Tomography (CT), a biopsy is often performed using bronchoscopy—a procedure that requires navigating a complex network of airways to reach the lesion. Navigation is challenging because the bronchial tree resembles a 3D maze of similar-looking passages. Developing an AI-based navigation system requires a dataset containing real bronchoscopy images, corresponding camera positions and orientations, and 3D airway models. However, such a dataset is not publicly available. To address this gap, in Multitel we have developed a pipeline for generating synthetic bronchoscopy datasets based on 3D airway models. Our pipeline generates realistic camera trajectories (i.e., positions) and orientations within the airways and renders virtual camera images by using the 3D graphics software Blender. Objective: The goal of this internship is to improve the realism and efficiency of our synthetic bronchoscopy dataset generation pipeline. Key Questions: How can we generate camera trajectories and orientations to better reflect real bronchoscope movements ? How can we enhance the rendering to produce images that closely resemble real bronchoscopy visuals ? How can we speed up the rendering operation without compromising the quality ? Tasks: Review existing methods for synthetic medical image generation. Improve the algorithms for trajectory and camera orientation generation. Enhance the rendering realism by refining textures, lighting, and scene composition. Exchange information with medical doctors to ensure that the solution is realistic and useful. Optimize the rendering process for speed and scalability. Document and present your findings to the AI team of Multitel. Expected Qualifications: proficiency in Python basic understanding of 3D geometry and transformations willingness to learn 3D modeling and rendering tools such as Blender interest in medical imaging and simulation strong oral and written communication skills in English Internship duration: min. 3 months CV and cover letter requiered You will work in a dynamic and welcoming environment. You’ll be part of a friendly and energetic team. We offer a stimulating and supportive work environment. Recognized as a center of excellence at the international level, Multitel develops and integrates emerging technologies in the industrial sector. These technologies are focused on five main areas of activity: Networks and Cybersecurity, Applied Photonics, Artificial Intelligence, Embedded Systems, and Railway Certification. Within the Artificial Intelligence department, the AI team holds a crucial role in supporting companies with their technological innovation projects, guiding them from the feasibility phase to the minimum viable product in various application fields such as aerospace, automotive, Smart Cities, Industry 4.0, medical sciences, defense, and more. We love fresh ideas, shared coffees, and motivated people. If you’re eager to learn fast and make a real impact, join us!