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to have a strong theoretical and numerical background in one or more of the following fields: Control theory and dynamical systems Theoretical Machine Learning Data science and information theory
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have taken specialized courses in some of the following disciplines: digital signal processing, audio signal processing, machine learning, and/or machine listening. Research experience (e.g. through
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resources. Applicants are expected to have a strong theoretical and numerical background in one or more of the following fields: Control theory and dynamical systems Theoretical Machine Learning Data science
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You have a master's degree in Computer Science, Artificial Intelligence or similar. You are interested in Logic, Machine Learning, Knowledge Graphs, Stream Processing, the Internet of Things, Edge
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machine learning is desirable LanguagesENGLISHLevelExcellent Additional Information Selection process Read the PhD Admission Requirements Choose your topics and look up the reference codes (2023-001). You
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-of-the-art molecular biology techniques, multimodal data generation and integration, gene regulatory network reconstruction and wide range of machine learning approaches The host labs will provide financial
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Description We are looking for several highly motivated PhD candidates with a background in photonics and an interest in machine learning or in combinatorial optimisation, for several research projects in
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, Agriculture Engineering (not agronomy), or Biosystems Engineering Basic knowledge in sensing technologies and measurement systems. Basic knowledge in machine learning, deep learning and/or data fusion and
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and measurement systems. Basic knowledge in machine learning, deep learning and/or data fusion and modelling tools, and eager to learn about more advanced modelling techniques. User of engineering
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-type specific samples, state-of-the-art molecular biology techniques, multimodal data generation and integration, gene regulatory network reconstruction and wide range of machine learning approaches