INTERNSHIP: BIOVIA Machine Learning Applications (Medical Imaging)
Join Dassault Systèmes BIOVIA and contribute to the development of innovative machine learning solutions that help scientists and researchers solve complex real-world challenges. As part of the Machine Learning team, you will work with BIOVIA's Pipeline Pilot AI platform to design, develop, and optimize advanced machine learning capabilities for scientific applications.
In this role, you will:
- Develop and enhance machine learning components within the BIOVIA Pipeline Pilot platform, supporting scalable scientific data processing workflows.
- Research, implement, and evaluate state-of-the-art deep learning algorithms for image analysis and scientific data processing applications.
- Collaborate with software engineers, product managers, quality assurance teams, and customer-facing teams to deliver high-quality solutions and innovative product features.
- Participate in the design, testing, and validation of machine learning workflows, ensuring performance, scalability, and reliability.
- Contribute to projects involving medical imaging, image annotation technologies, model optimization, workflow automation, and emerging AI methodologies such as federated learning.
- Support automated testing initiatives and help maintain high software quality standards across developed functionalities.
Potential project areas may include:
- Medical imaging quality control and automated MRI validation.
- Deep learning model optimization and deployment.
- Image annotation tools and continuous learning workflows.
- Federated learning and privacy-preserving AI.
- Scientific image processing and workflow automation.
- Development of scalable AI-driven capabilities within Pipeline Pilot.
Education
- Currently pursuing a Master's or PhD degree in Computer Science, Data Science, Electrical Engineering, Biomedical Engineering, or a related technical discipline.
- Must remain actively enrolled in an accredited university throughout the internship.
- Minimum cumulative GPA of 3.0.
Experience & Technical Skills
- Experience with machine learning and deep learning techniques, particularly for image and/or tabular data.
- Proficiency in Python programming.
- Hands-on experience with machine learning frameworks such as TensorFlow and/or PyTorch.
- Familiarity with scientific computing and data processing libraries including NumPy, pandas, scikit-learn, and OpenCV.
- Understanding of statistical analysis, data-driven modeling, and machine learning principles.
- Exposure to machine learning model training, deployment, or workflow automation is preferred.
- Knowledge of medical imaging workflows, image processing techniques, or annotation tools is a plus.
Behavioral Skills
- Strong analytical and problem-solving capabilities.
- Scientific curiosity and passion for innovation.
- Excellent collaboration and teamwork skills.
- Strong verbal and written communication abilities.
Commitment to delivering high-quality software and technical solutions.
- Opportunity to work on cutting-edge AI and machine learning technologies applied to scientific research and industry challenges.
- Exposure to BIOVIA's industry-leading Pipeline Pilot platform and advanced software development practices.
- Collaborative environment with experienced engineers, researchers, and product leaders.
- Hands-on experience contributing to impactful projects used by customers worldwide.
- Professional development opportunities and mentorship from experts in machine learning and scientific software development.
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