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the supervision of dr. ir. Mathias Peirlinck and dr. ir. Aimée Sakes. The Peirlinck Lab integrates multimodal experimental data, physics-based modeling, and machine learning techniques to understand, explore, and
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stages of their careers and offering competitive compensation. We are also dedicated to providing a supportive and inclusive working environment where you can learn and grow every day. Additionally, you
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of health data or for decision making in health care. You will be developing innovative models, data-driven algorithms, and/or machine learning-based approaches with the goal of profoundly impacting health
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of applied cryptography, deep learning methods that are immune to common side-channel defences, machine learning algorithms that can operate on encrypted data in the cloud, detection and mitigation of large
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responsible for the maintenance and optimisation of our nanofabrication equipment. You will also instruct users to safely use the equipment and assist them in case of defects or disruptions. As a processing
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Timing, related to their expertise Develop Observing System Data Science (Delft observation theory, artificial intelligence, machine learning, distributed computing) Be an expert and advisor on reference
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of our department. You will learn how we setup and maintain them. You will learn how the machines are used by our researchers. What software is used for IC design and Deep learning. As your expertise grows
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with world-changing potential. We’re developing scalable prototypes of a quantum computer and a secure quantum internet. We believe quantum technology will be a game changer in many social and economic
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Join us on our quest to overcome a long-standing research challenge in soft tissue biomechanics through the combination of multi-modal experimental tissue testing data, machine learning and physics
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The mission of TU Delft's Quantum and Computer Engineering (QCE) department is to invent, design, prototype and demonstrate the potential of disruptive computing engines by harnessing unique