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About SecurEL SecurEL is a Centre for Environment-friendly Energy Research, facilitating a secure, resilient, and sustainable electricity distribution grid that ensures both the security of electricity
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focus on how interactions between species at different trophic levels shape these responses. The project combines (1) analysis of long-term datasets to quantify historical changes in the distributions
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Background in probabilistic methods Experience with the application of AI algorithms and probabilistic methods Good programming skills Personal characteristics To complete a doctoral degree (PhD), it is
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of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning
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fuel cells with the vessel’s onboard DC distribution grid (1-1.5 kV or even MV) require power electronics, which enable power and voltage control. Designing high-efficiency and low-footprint power
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of climate-friendly transport solutions may affect how companies and public sector entities are distributed in space, both within and between regions. This raises questions about how and to what extent a
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is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete research training to the level of a doctoral
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variables need to be connected to variables that are observable in the laboratory. Of special interest is the information entropy that characterizes the flow distribution, velocity distribution and the