18 Statistics-"Maastricht-University" positions at Delft University of Technology in Netherlands
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PhD position in the area of Multivariate dependence modelling and statistical machine learning algorithms for patient risk profiling. In partnership with RECENTRE (see https://www.4tu.nl/recentre/), a
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their performance. To achieve this, you will use your skills in advanced mathematical and statistical techniques. The project is situated in the context of efficient online learning, with a focus on scaling with
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optimize the qubit performance by gathering statistics on qubit quality. Moreover, you will largely automate this process. Your conclusions and feedback will enable the design, fabrication, and operation of
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"with memory" are of importance in several disciplines, such as for financial and statistical modelling. However, due to the correlation structure their computational simulation is very challenging
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Learning, Artificial Intelligence, or a related field. Demonstrate a strong mathematical foundation in optimization, statistical learning, and probability. Possess a thorough understanding of machine
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, statistics, life sciences or a similar area. You possess a strong background in data analytics and machine learning methods. You enjoy gaining, combining, and translating knowledge from multiple fields and
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challenges in such large-scale distributed networks i.e., the low-cost sensing, decentralized statistical inference, distributed control and online decision making. These distributed systems will have to fuse
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particles to shifts of prevailing cloud regimes in response to changing weather statistics. During your PhD research, you will explore concepts from complex systems theory and data-driven approaches
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) on the other hand. We use tools from statistical physics, information theory and non-linear dynamics to understand the how well a particular system responds to a stimulus, and how this stimulus is processed
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keen interest in uncertainty modelling, probability theory and statistics. You thrive on conducting research geared to real-world application in the security domain and are intrinsically motivated