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Field
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the position and why you are especially qualified for it. Your workplace You will be employed in the Reasoning and Learning Lab (ReaL), Division of Artificial Intelligence and Integrated Computer Systems (AIICS
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workplace You will be employed in the Reasoning and Learning Lab (ReaL), Division of Artificial Intelligence and Integrated Computer Systems (AIICS) at the Department of Computer and Information Science (IDA
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writing and implementing code alongside extracting information, trends, and patterns from large datasets. Topics to explore during this PhD project include: Investigating available software options Methods
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statistics, together contributing to a deeper understanding of the basis of human brain connectivity and brain function. You have affinity with working with large datasets and have knowledge of data analysis
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working on challenging theoretical and practical problems in Safe Machine Learning. Specifically, we are looking for a student to address the following research problem in their PhD thesis: 1
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Environment - Wiley Online Library Additive Manufacturing: A Comprehensive Review Big data, machine learning, and digital twin assisted additive manufacturing: A review - ScienceDirect Full article: Achieving
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
to anticipate and manage. This PhD will develop a machine learning module to detect early warning signals of positive tipping points from techno-economic data, helping policymakers design adaptive strategies
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advanced seismic methods (including array processing, machine learning, and potentially distributed acoustic sensing) to develop novel approaches for monitoring unsteady and non-uniform flood flows across
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Investment technology, ethics and strategy Equity and other asset classes Financial econometrics and machine learning. Corporate finance and accounting Corporate governance and shareholder value Corporate
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application! We are looking for a PhD student in AI and machine learning with a focus on generative machine learning methods for cyber security applications. Your work assignments The primary focus of this PhD