146 machine-learning-and-image-processing-"RMIT-University" PhD positions in Netherlands
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, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost
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of Sight - How Visual Processing Develops in Brains and Machines. For animals, it is imperative to learn as quickly as possible. To do this, we know that the mammalian visual system utilizes "inductive
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description This project addresses the effective design of a military supply logistics network, composed of transportation and communication links such as roads and rail, aerial drone routes, and nodes, such as
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single mirror image forms is often denoted as “A Signature of Life”. Homochirality is essential for, e.g., molecular recognition and information processing, enzyme functioning and cell replication. However
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score of at least 237 on the computer-based form of the Test of English as a Foreign Language (TOEFL); or A score of at least 92 on the internet-based test of the Test of English as a Foreign Language
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procedure. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development
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are environmentally sustainable. To this end, different designs of AI systems should be assessed during the design phase. Data flow diagrams used at NOLAI capture the processing, storage and
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that activity-silent mechanisms, such as short-term synaptic plasticity, also play an important role. We will experimentally target these two mechanisms, using EEG in combination with machine learning to reveal
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. Proficiency in geospatial, 3D, and image-processing software for data collection and analysis. Experience working with GIS, QField, total stations, geophysical equipment, and drones. Experience in stratigraphic
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant