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Field
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deep-learning and 3D computer-vision models that detect features while representing a distribution of plausible interpretations. Encode geological relationships in a knowledge graph that stores
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to players’ needs in real time. The successful candidate will work with an interdisciplinary supervisory team, benefiting from expertise in adaptive systems, accessibility and human-computer interaction, and
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| Electrical and Computer Engineering Conducts advanced research and development in the Department of Electrical & Computer Engineering, with a primary focus on cathodoluminescence spectroscopy and the
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The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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various relevant computer software applications. • Assist with literature research, editing and preparing manuscripts, scientific illustrations and computer graphics for publication. • May perform
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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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considered. Education related to Artificial Intelligence (AI), robotics programming, computer vision, Design for Manufacturing and Assembly (DfMA), or life cycle environmental/cost assessment is considered
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electrophysiology The student will join a highly collaborative environment involving clinicians, engineers, mathematicians, and computer scientists, with access to unique clinical datasets and state-of-the-art
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position