Master Thesis efficient and Secure Deep Learning Image Descriptors
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As **Austria's largest research and technology organisation** for applied research, we are dedicated to make substantial contributions to solving the major challenges of our time, climate change and digitalisation. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture of innovation and our motivated, international teams, we are working to position AIT as Austria's leading research institution at the highest international level and to make a positive contribution to the economy and society.
MASTER THESIS "EFFICIENT AND SECURE DEEP LEARNING IMAGE DESCRIPTORS"
CENTER FOR VISION, AUTOMATION & CONTROL
- You closely work with our researchers and engineers, who focus on the **development and deployment of assistive and autonomous systems**, particularly in the area of robust and accurate localisation and positioning.
- Under the guidance of our experts, you **contribute to the development of cutting-edge methodologies in deep learning**-based image descriptors, balancing efficiency, and security on resource-constrained edge devices.
- You **investigate state-of-the-art deep learning advancements** in descriptor optimisation and privacy-aware techniques, identifying gaps and proposing innovative solutions.
- You **design, implement, and optimise deep learning models** to extract robust and privacy-preserving image descriptors efficiently on resource-constrained devices.
- You **benchmark and evaluate model performance**, improving robustness, efficiency, and privacy-preserving capabilities across varied scenarios.
- You **exchange insights with interdisciplinary and international experts** in machine learning and computer vision, contributing to a dynamic and collaborative environment.
- You document your results, with the **potential to present your work in conference** proceedings or **publish it** in peer-reviewed journals.
**Your qualifications as an Ingenious Partner**:
- Ongoing master's studies in the field of Computer Science, Robotics, or Applied Mathematics
- Solid knowledge of Python or C++
- Experience with PyTorch/ExecuTorch (formerly PyTorch Mobile) or TensorFlow/LiteRT (formerly TensorFlow Lite)
- Knowledge of computer vision is advantageous
- Experience with edge computing is advantageous
- Proficiency in English, both spoken and written
**What to expect**:
- **Duration of the master’s thesis project**: 6 months
- **Start date**: ideally 01.03.2025 or 01.04.2025 EUR 1002,
- gross per month for 20 hours/week based on the collective agreement. There will be additional company benefits. As a research institution, we are familiar with the supervision and execution of master theses, and we are looking forward to supporting you accordingly
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