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, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems. Project description This PhD project is linked
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environments. The group consists of approximately 10 members including scientists, engineers and postdocs who are actively driving multiple in-house research/development projects, among which are time-resolved
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. Presently around 100 people, including 35 PhD students and 15 postdocs, in 25 research groups work at DEEP. For more information about us, please visit: the Department of Ecology, Environment and Plant
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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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, signal processing and/or wireless communication. Basic knowledge of and/or experience in working with reinforcement learning/other machine learning algorithms Excellent command of spoken and written
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medicine in sepsis. The group consists of senior researchers, postdocs, and PhD students with expertise in clinical medicine, cell and molecular biology, proteomics, and bioinformatics. Within the research
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and
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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics