Internship - Self-supervised learning and pathology foundation models

Want to help invent the future? Barco Labs is the innovation engine of Barco, where new technologies, concepts, and ideas are explored long before they become products. About the internship At Barco Labs, you'll work on innovative research projects at the intersection of AI and digital pathology, helping shape the future of medical imaging. During this internship, you will explore how state-of-the-art foundation models and self-supervised learning techniques can be applied to large-scale digital pathology images. Your work will focus on leveraging pre-trained image representations to analyse tissue content and detect image quality issues, without relying on extensive annotated datasets. You will contribute to the evaluation and development of AI-driven approaches for identifying artifacts introduced during slide preparation and image acquisition, helping improve the reliability of digital pathology workflows. What we're looking for Master student in Computer Science, Artificial Intelligence, Data Science, Biomedical Engineering, or a related field Strong programming skills in Python Basic knowledge of machine learning and deep learning Experience with PyTorch, TensorFlow, or similar frameworks Strong analytical and problem-solving skills Interest in scientific research and experimentation Experience with Linux/Docker Experience with Git (GitHub) and collaborative software development Experience with LLM in development Fluent spoken and written communication in English Experience with computer vision, foundation models, representation learning, medical imaging, or large-scale AI training is a plus. What we offer At Barco Labs, you will collaborate with experienced researchers and engineers working on next-generation healthcare solutions. You'll gain hands-on experience with state-of-the-art AI technologies, large-scale image datasets, and real-world challenges that have a direct impact on pathology diagnostics and healthcare innovation.