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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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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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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
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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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) developing and validating preprocessing pipelines; (3) architecting and comparing spectral-only and multimodal (HSI + NIR + Raman + RGB) deep-learning models; (4) implementing robust sensor-fusion strategies
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models. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience a and strong deep learning programming skills. Ability to work in an
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ultrabroadband mid-infrared intrapulse difference frequency generation sources. You will perform multispecies detection in demanding applications such as environmental and exposure monitoring, and in the green