52 machine-learning-and-image-processing-"RMIT-University" PhD positions at University of Groningen
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located across 5 European countries. MonaLisa is at the forefront of artificial molecular machine research, setting the stage for breakthroughs in chemical synthesis, nanotechnology, medical treatment and
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garments into recycle, reuse, and manual-review streams; this PhD project tackles the core challenge of designing and optimizing a high-throughput hyperspectral imaging system, fused with complementary
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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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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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
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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation