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application of cutting-edge causal machine learning methods You will further elaborate and concretise the PhD theme and research tasks at the start of the PhD in consultation with the supervisor and any co
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the following elements: Abstract (max 250 words) The abstract of a PhD research plan should serve as a concise summary of the key elements of your proposed research. It should provide an overview
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are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation
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regulatory network reconstruction and wide range of machine learning approaches The host labs will provide financial support for the whole length of the PhD. The applicant will be expected to seek independent
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experience with scientific computing, data analysis, machine learning and/or AI You have an interest in environmental sustainability and pharmaceutical production Considered a plus: You have experience with
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(100%) PhD in the field of Molecular and Computational Neurogenomics Position We are a highly motivated international team of researchers at the Molecular Neurogenomics group (Jordanova Lab) and the
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partnership with the Odysseus Space company as part of the Simulator development for the optical slant path program. This PhD project aims to develop an analysis tool for the optical ground-to-satellite links
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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interest in user-centered security, human factors in security, human computer-interaction or UX. Academic: A Master in Cybersecurity or equivalent degrees with expertise in cybersecurity assessment or a
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insight in how to integrate the developed logic framework in hybrid computational intelligence / machine learning approaches. For that purpose, a use case handling the measurement of the confidence