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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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, 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
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, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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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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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations