Medis Medical Imaging is driven by a bold ambition: to transform complex cardiovascular imaging into intuitive software that enables medical professionals to work smarter, faster, and with greater confidence. For over 30 years, Medis has pioneered advanced imaging tools, making them accessible to researchers and clinicians worldwide. Today, we build on this legacy with a forward‑looking roadmap powered by AI innovation.
Working at Medis is both purposeful and inspiring. You’ll be part of a fast‑paced, innovation‑led company with a global presence, rooted in a strong heritage and a pioneering spirit. Our culture is built by smart, hands‑on people who take ownership and care deeply about their work and each other. We value connection, curiosity, and collaboration. We take pride in delivering technology that truly makes a difference.
What will your role be?The internship centres around our ED (End‑Diastolic) Detection Algorithm, a critical component in automating frame selection in X‑ray angiograms. This algorithm leverages deep learning models to predict cardiac phases and identify ED frames without relying on ECG signals, enhancing reproducibility and efficiency in clinical workflows.
Internship Goals:- Modernize the ED detection repository using the latest frameworks and coding standards.
- Investigate opportunities for performance improvements and algorithmic enhancements.
- Extend the algorithm’s capabilities to detect additional features such as table movement from image sequences.
- Currently pursuing a Master’s degree (or an advanced Bachelor’s) in Computer Science, Artificial Intelligence, Biomedical Engineering, or a related field.
- Have hands‑on experience with Python, as well as with PyTorch and/or TensorFlow.
- Have a solid understanding of the basics of computer vision, with a keen interest in applying it to healthcare.
- Comfortable working with version control (Git) and modern software development practices.
- Prior experience with medical imaging data or time‑series/image sequence analysis is a plus.
- Comfortable working in English and available for a hybrid internship based in the Netherlands (with at least 2 days on‑site weekly). Candidates must reside in the Netherlands.
- Ability to commit to a full‑time, 6‑month internship.
- Committed and pro‑active.
- Accurate, reliable, and detail oriented.
- Strong analytical and problem‑solving skills.
- Excellent communication and teamwork skills.
- A dynamic, hands‑on internship where you’ll work on real‑world software projects that emphasize collaboration.
- Mentorship and collaboration with an international, diverse, and multidisciplinary team.
- A hybrid working environment, balancing remote flexibility with in‑person collaboration.
- The chance to develop practical expertise in developing production‑ready Deep Learning models.
- A competitive internship allowance and reimbursement for travel expenses.