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tools, including 4D point cloud modeling and state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier
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machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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, and you will join the research group led by Prof. Christa Cuchiero to work at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The research areas cover a wide range of
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and interventional datasets in high dimensions. Our interdisciplinary approach integrates interpretable machine learning, statistics, algorithms, and single-cell multi-omics. Position Overview You will
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experience. Experience with one or more of the following: genetic cloning, protein expression, purification and characterization, mass spectrometry, NMR. Experience with and/or demonstrated ability to learn
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): project Management or Project Studies (with strong computational/AI expertise) systems Engineering or Control Systems (with applications to large-scale projects) artificial Intelligence / Machine Learning
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. The primary objective is to design robust and efficient planning solutions—integrated within a digital twin—that account for the uncertainties and variability inherent in industrial processes. Machine learning
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related field Demonstrated experience in interdisciplinary research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong
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oriented field relevant to the project, such as computer science, mathematics, statistics or physical sciences. Expertise in machine learning based and statistical data analysis, including the capability
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, concentration and functional inequalities • Mathematical aspects of machine learning and deep neural networks • Free Probability aspects of Quantum Information Theory. While excellent candidates with other