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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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(Wissenschaftszeitvertragsgesetz - WissZeitVG). A shorter contract term is possible by arrangement. The position aims at obtaining further academic qualification. Professional assignment: Chair of Machine Learning for Spatial
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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PhD Scholarship Opportunities in Optoelectronic Semiconductors at the Faculty of Engineering and Faculty of Science (Multiple Positions) Job No.: 682543 Location: Clayton campus Employment Type
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approaches, including Low Impact Development (LID) practices (e.g., green roofs, rain gardens), with a specific focus on urban catchments. The research will place a strong emphasis on machine learning
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student, you will be supported by a multidisciplinary team with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected
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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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generated data sets of different sizes and measuring the environmental impact. This impact can be measured and calculated by our Software Energy Lab, which has multiple test machines with GPUs and AI