Enhance AI Model Security through Federated Learning Research
4 uur geleden
Federated learning is a technique that enables AI model training with data from multiple parties without centralizing the data. However, research has shown that private data can still be reconstructed from the model via inversion attacks. We're seeking a talented individual to explore vulnerabilities in current state-of-the-art algorithms for FL and mitigate these weaknesses.
Company OverviewTNO is a pioneering organization dedicated to developing groundbreaking applications in computer vision. Our Intelligent Imaging department is a passionate team of professionals specializing in AI and deep learning. With diverse backgrounds ranging from the medical field to artificial intelligence, we strive to push the boundaries of innovation.
Job DescriptionYou will start by conducting a literature study to understand the current state-of-the-art approaches on FL systems. Next, you'll investigate solutions to improve protection against inversion attacks, focusing on applying FL on computer vision applications. Optionally, you can contribute to a scientific paper on this topic.
Required Skills and Qualifications- A master's degree in artificial intelligence, computer science, physics, mathematics, electrical engineering, or a related field.
- Experience in computer vision, artificial intelligence, deep learning, and Python programming.
We offer a highly professional internship environment within a team of top experts. You'll receive:
- A suitable internship allowance (approximately €1000 per month for a full-time internship).
- Possibility of eight hours of free leave per internship month.
- A free membership of TNO's sports activities and courses.
- Use of a laptop.
- An allowance for travel expenses.
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