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and supervise PhD and MSc student projects). Qualification: Background in concrete technology and characterisation. Background within image processing, computer vision, or related fields. Background
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student projects). Qualification You should have a background within deep learning, big-data, computer vision, or related fields, as well as experience in in-line process monitoring or similar areas
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, electrical engineering, etc. Prior experience in (1) image processing, particularly for radiographic and computed tomographic data as well as mesh-type data, and (2) machine learning, particularly deep
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with 3D data processing or point cloud analysis Familiarity with machine learning or data-driven modelling approaches Ability to work independently and collaboratively in an interdisciplinary research
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If you want to pursue a research career at the intersection of additive manufacturing (AM), microstructural engineering and advanced statistical/machine-learning (ML) based modelling, then this PhD
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technology and characterisation. Background within image processing, computer vision, or related fields. Background within in-line process monitoring or related fields. Furthermore, it is an additional
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13C incubation approaches the current project will quantify dark carbon fixation rates in deep ocean settings and explore how environmental parameters affect the process rates. These approaches
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workflows Experience in quantitative data analysis and computational approaches; familiarity with machine learning or advanced statistal methods is advantageous Preferably experience with micro-CT imaging
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will develop atomistic models and machine-learning potentials to interpret experimental data and predict catalytic performance. The tasks can include Advancing equivariant neural network potentials
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural