Internship - Evaluation of Uncertainty in Deep Learning Based Computer Vision
il y a 2 semaines
**Internship Context Description**
Deep learning has recently emerged as a major breakthrough across various domains, including computer vision for medical image analysis. These advancements have significantly improved the potential accuracy and efficiency as proven on different published academics works.
However, they still suffer limitations when considering a transfer to reliable medical devices for daily use in clinics. In particular, deep learning models are often overconfident in their predictions and lack self-awareness of their own limitations. This is particularly critical when dealing with out-of-distribution elements or samples close to decision boundaries. Addressing these challenges is essential for developing reliable AI systems in medical imaging. This is particularly true in the field of ultrasound imaging, which significantly differ from the natural images that constitutes the main publicly available computer vision datasets that serve as basis for mainstream academic publications in the field. We aim at developing specific methodologies and tools in order to tackle this problem for offering trustworthy AI-based medical models that can serve practitioners in their daily clinical work, improving the patients benefits.
**Position Overview**
We are seeking a highly motivated intern to join our research and development team. The focus of this internship is on the evaluation of uncertainty in computer vision tasks, specifically classification and detection, within the context of ultrasound medical imaging. This role offers a unique opportunity to work at the intersection of classical computer vision, deep learning, signal processing and medical imaging. The uncertainty in deep learning is a hot topic with many links to other computer vision problem in academics and industry.
**Key Responsibilities**
- Develop and implement deep learning related evaluation of uncertainty in ultrasound image for classification and detection tasks.
- Integrate classical computer vision techniques to enhance model performance and reliability.
- Conduct experiments to assess the robustness and accuracy of AI models in clinical settings.
- Collaborate with a multidisciplinary team of engineers, data scientists, and medical professionals.
- Document research findings and contribute to scientific publications.
**Required Skills**:
- Strong foundation in classical computer vision and deep learning.
- Proficiency in signal processing techniques and general computer science.
- Experience with programming languages such as Python and frameworks like TensorFlow or PyTorch.
- Familiarity with medical imaging modalities, particularly ultrasound, is a plus but not mandatory.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- English is a must have (reading/writing/speaking).
**What We Offer**
- An innovative and collaborative work environment.
- Competitive salary
- A cutting-edge infrastructure for AI model development, using our own dedicated GPU server and workstations
- Hands-on experience with state-of-the-art AI technologies in the medical field.
- Mentorship from experienced professionals in AI and medical imaging.
- Minimum 5 months - Maximum 6 months position
- The possibility of extending the internship into a PhD thesis, providing a pathway to further academic and professional development.
**Job Type**: Internship
Contract length: 6 months
Pay: 700.00€ - 800.00€ per month
**Education**:
- Bachelor's (preferred)
Work Location: In person
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