Due to their performance, machine and deep learning algorithms are increasingly being deployed in a wide range of applications. However, to ensure their safe and effective use in critical domains, these models must also be trustworthy. Trustworthy AI encompasses several key aspects, including explainability, robustness, and uncertainty quantification (UQ). Uncertainty quantification methods make it possible to produce prediction intervals instead of generic point estimates. This is crucial, as it provides insights into the model's confidence in its predictions. Such information can guide the need for human expert intervention or allow the model to adjust its behavior safely when confidence is low. Conformal prediction is one approach to obtain such prediction sets. It is particularly promising because it provides post-hoc, distribution-free guarantees on a model's predictions. This means that conformal prediction methods can be applied to any pre-trained model, regardless of its architecture or training procedure, while still providing valid uncertainty estimates, crucial for real-world applications and stakeholders. The intern will play a key role by exploring and developing state-of-the-art conformal methods for computer vision and image generation. The main targeted applications include semantic image segmentation, object detection, image generation, and instance segmentation. The intern will work closely with AI experts from the Fundamental AI group at Multitel. The main responsibilities include: Performing a literature review of conformal prediction methods for computer vision and image generation; Contributing to the development of a Python framework implementing the most relevant conformal prediction methods; Benchmarking methods on relevant datasets; Synthesizing key findings into a detailed report; Presenting results to the AI team. Expected qualifications: Strong ability to identify innovative techniques through thorough literature review. Proficiency in Python programming, particularly with PyTorch. Ability to translate mathematical concepts into functional code. Duration: from 4 to 6 months. CV and cover letter required. 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 centre 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!