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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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Join us to explore the mechanics of soft matter through a unique blend of theory, hands-on experiments, and machine learning. Job description Soft matter such as polymers and hydrogels
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challenges. As a part of your PhD research you will regularly visit our industrial and scientific partners to learn about the challenges and constraints. You will also study the problem in detail with
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intersection of mechanics, materials, and machine learning. Collaboration with international experts from diverse disciplines. Access to cutting-edge computational and experimental facilities. Supervision of MSc
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning
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aims to rethink how soft robots can interact with their environment, focusing on large-area, multi-point contacts—similar to how an elephant wraps its trunk around an object. Unlike traditional robots
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… Requirements Specific Requirements Your profile includes - A Bachelor and Masters degree in law preferably with a strong technology law profile - Proven research skills and a deep understanding of the Law and
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trunk around an object. Unlike traditional robots, which rely on rigid links and localized interaction points, soft robots are composed of deformable materials that can conform to complex geometries and
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-based infrared sources is emerging as a promising and effective tool. In particular, the newly developed high-power intrapulse difference frequency generation (IDFG) based sources extend deep into the mid
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large-scale neural models of the early visual system. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience and strong deep learning