Deep Learning Intern
Medis Medical ImagingNetherlands22 hours ago
InternshipRemote FriendlyResearch
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Who are we?
At Medis we believe in empowering medical professionals with our innovative analytical solutions. For more than 35 years, cardiologists, radiologists, researchers and industry partners worldwide rely on Medis post-processing software, resulting in customers in more than 40 countries. Our team takes pride in providing innovative cardiovascular imaging solutions that support our customers' diagnoses and treatment options. We provide medical professionals with worldwide support, so together we can improve patients' quality of care.
Our headquarters is in Leiden, but over the years we have established subsidiaries and branch offices in the USA, Japan, Germany, France, and the United Kingdom, as well as distributors and local agents in multiple countries.
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:
At Medis we believe in empowering medical professionals with our innovative analytical solutions. For more than 35 years, cardiologists, radiologists, researchers and industry partners worldwide rely on Medis post-processing software, resulting in customers in more than 40 countries. Our team takes pride in providing innovative cardiovascular imaging solutions that support our customers' diagnoses and treatment options. We provide medical professionals with worldwide support, so together we can improve patients' quality of care.
Our headquarters is in Leiden, but over the years we have established subsidiaries and branch offices in the USA, Japan, Germany, France, and the United Kingdom, as well as distributors and local agents in multiple countries.
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 beginning in February
- 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
Key Skills
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